{"timestamp":"2025-09-22T13:27:50.247Z","type":"session_meta","payload":{"id":"0199719b-e14a-7581-bb92-8f5b7cd69a49","timestamp":"2025-09-22T13:27:45.226Z","cwd":"c:\\GitCode\\paiban","originator":"codex_vscode","cli_version":"0.39.0","instructions":"﻿# Repository Guidelines\r\n\r\n## Project Structure & Module Organization\r\nSource lives under the solution `NPP.SmartSchedue.sln`. `NPP.SmartSchedue.Host` hosts the ASP.NET Core app, with environment settings in `appsettings*.json`, seed scripts in `ConfigCenter` and `InitData`, and static assets in `wwwroot`. Domain services sit in `NPP.SmartSchedue.Api`, organized into `Core` (attributes, constants), `Services` (business logic), and `Repositories` (data access). Shared contracts, DTOs, and interfaces reside in `NPP.SmartSchedue.Api.Contracts`; keep cross-project types there. Tests are in `NPP.SmartSchedue.Tests`, with reusable fixtures in `BaseTest` and service-focused integration suites under `Services`.\r\n\r\n## Build, Test, and Development Commands\r\n- `dotnet restore NPP.SmartSchedue.sln` restores all project dependencies.\r\n- `dotnet build NPP.SmartSchedue.sln -c Release` validates compilation; use `-c Debug` during local iteration.\r\n- `dotnet run --project NPP.SmartSchedue.Host` boots the API with the default profile; add `--launch-profile Development` when you need local CAP setups.\r\n- `dotnet test NPP.SmartSchedue.Tests/NPP.SmartSchedue.Tests.csproj --logger \"trx;LogFileName=test-results.trx\"` exercises the xUnit suites and saves artifacts for PR review.\r\n\r\n## Coding Style & Naming Conventions\r\nTarget .NET 9 defaults: four-space indentation, braces on new lines, and explicit namespaces. Use `PascalCase` for classes, public members, and DTOs, `camelCase` for locals and private fields, and prefix interfaces with `I` as seen in `Api.Contracts`. Suffix asynchronous methods with `Async`, and keep request/response models in the Contracts project. Run `dotnet format` before committing to enforce spacing and using-order consistency.\r\n\r\n## Testing Guidelines\r\nWrite xUnit tests alongside existing patterns such as `EquipmentMaintenanceIntegrationTest`. Name new files `{Feature}Test.cs` or `{Feature}IntegrationTest.cs`, group helper logic in `BaseTest`, and rely on `Microsoft.AspNetCore.Mvc.Testing` for host bootstrapping. Aim to cover new service paths and repository edge cases; add mocks via Moq where external systems (CAP, RabbitMQ, MySQL) would otherwise be required.\r\n\r\n## Commit & Pull Request Guidelines\r\nPrefer descriptive commits (`feat(scheduling): add notification workflow`) instead of numeric placeholders seen in recent history. Bundle related changes, include migration or config adjustments in the same commit, and reference tracking IDs where relevant. Pull requests should outline the change, list manual or automated test evidence, mention configuration impacts (CAP, FreeSql, message queues), and supply screenshots for any UI updates under `wwwroot`.\r\n\r\n## Configuration & Environment Notes\r\nKeep secrets out of `appsettings.json`; use user secrets or environment variables for connection strings and CAP brokers. Document any required RabbitMQ or MySQL endpoints in the PR. When adding assets or scripts, mirror the structure under `ConfigCenter`, `InitData`, and `wwwroot` so the publish targets continue copying them correctly.\r\n"}}
{"timestamp":"2025-09-22T13:27:50.248Z","type":"response_item","payload":{"type":"message","role":"user","content":[{"type":"input_text","text":"<user_instructions>\n\n﻿# Repository Guidelines\r\n\r\n## Project Structure & Module Organization\r\nSource lives under the solution `NPP.SmartSchedue.sln`. `NPP.SmartSchedue.Host` hosts the ASP.NET Core app, with environment settings in `appsettings*.json`, seed scripts in `ConfigCenter` and `InitData`, and static assets in `wwwroot`. Domain services sit in `NPP.SmartSchedue.Api`, organized into `Core` (attributes, constants), `Services` (business logic), and `Repositories` (data access). Shared contracts, DTOs, and interfaces reside in `NPP.SmartSchedue.Api.Contracts`; keep cross-project types there. Tests are in `NPP.SmartSchedue.Tests`, with reusable fixtures in `BaseTest` and service-focused integration suites under `Services`.\r\n\r\n## Build, Test, and Development Commands\r\n- `dotnet restore NPP.SmartSchedue.sln` restores all project dependencies.\r\n- `dotnet build NPP.SmartSchedue.sln -c Release` validates compilation; use `-c Debug` during local iteration.\r\n- `dotnet run --project NPP.SmartSchedue.Host` boots the API with the default profile; add `--launch-profile Development` when you need local CAP setups.\r\n- `dotnet test NPP.SmartSchedue.Tests/NPP.SmartSchedue.Tests.csproj --logger \"trx;LogFileName=test-results.trx\"` exercises the xUnit suites and saves artifacts for PR review.\r\n\r\n## Coding Style & Naming Conventions\r\nTarget .NET 9 defaults: four-space indentation, braces on new lines, and explicit namespaces. Use `PascalCase` for classes, public members, and DTOs, `camelCase` for locals and private fields, and prefix interfaces with `I` as seen in `Api.Contracts`. Suffix asynchronous methods with `Async`, and keep request/response models in the Contracts project. Run `dotnet format` before committing to enforce spacing and using-order consistency.\r\n\r\n## Testing Guidelines\r\nWrite xUnit tests alongside existing patterns such as `EquipmentMaintenanceIntegrationTest`. Name new files `{Feature}Test.cs` or `{Feature}IntegrationTest.cs`, group helper logic in `BaseTest`, and rely on `Microsoft.AspNetCore.Mvc.Testing` for host bootstrapping. Aim to cover new service paths and repository edge cases; add mocks via Moq where external systems (CAP, RabbitMQ, MySQL) would otherwise be required.\r\n\r\n## Commit & Pull Request Guidelines\r\nPrefer descriptive commits (`feat(scheduling): add notification workflow`) instead of numeric placeholders seen in recent history. Bundle related changes, include migration or config adjustments in the same commit, and reference tracking IDs where relevant. Pull requests should outline the change, list manual or automated test evidence, mention configuration impacts (CAP, FreeSql, message queues), and supply screenshots for any UI updates under `wwwroot`.\r\n\r\n## Configuration & Environment Notes\r\nKeep secrets out of `appsettings.json`; use user secrets or environment variables for connection strings and CAP brokers. Document any required RabbitMQ or MySQL endpoints in the PR. When adding assets or scripts, mirror the structure under `ConfigCenter`, `InitData`, and `wwwroot` so the publish targets continue copying them correctly.\r\n\n\n</user_instructions>"}]}}
{"timestamp":"2025-09-22T13:27:50.248Z","type":"response_item","payload":{"type":"message","role":"user","content":[{"type":"input_text","text":"<environment_context>\n  <cwd>c:\\GitCode\\paiban</cwd>\n  <approval_policy>never</approval_policy>\n  <sandbox_mode>danger-full-access</sandbox_mode>\n  <network_access>enabled</network_access>\n  <shell>powershell.exe</shell>\n</environment_context>"}]}}
{"timestamp":"2025-09-22T13:27:50.248Z","type":"response_item","payload":{"type":"message","role":"user","content":[{"type":"input_text","text":"# Context from my IDE setup:\n\n## Active file: NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\n\n## Active selection of the file:\nLinearProgrammingEngine\n## Open tabs:\n- LinearProgrammingEngine.cs: NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\n\n## My request for Codex:\n分析 LinearProgrammingEngine， 总结当前的引擎\n"}]}}
{"timestamp":"2025-09-22T13:27:50.248Z","type":"event_msg","payload":{"type":"user_message","message":"# Context from my IDE setup:\n\n## Active file: NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\n\n## Active selection of the file:\nLinearProgrammingEngine\n## Open tabs:\n- LinearProgrammingEngine.cs: NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\n\n## My request for Codex:\n分析 LinearProgrammingEngine， 总结当前的引擎\n","kind":"plain"}}
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{"timestamp":"2025-09-22T13:27:55.594Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Preparing to read file content**"}}
{"timestamp":"2025-09-22T13:27:57.467Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":3352,"cached_input_tokens":2432,"output_tokens":258,"reasoning_output_tokens":192,"total_tokens":3610},"last_token_usage":{"input_tokens":3352,"cached_input_tokens":2432,"output_tokens":258,"reasoning_output_tokens":192,"total_tokens":3610},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:27:57.467Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Preparing to read file content**"}],"content":null,"encrypted_content":"gAAAAABo0U7cqi1ONE0e1Ul4JHgTkzKon5uktfdiwI32bRUPmOgSxcuKBoOiR08fNLumKgL7RKFEVnyuW6DUv8nNOd_aoLfLt4DaYtFg86c85D-zTK2ECmYYb-Ut4DYJlkcoL56ITcRcI6aLEEV5k47CY4JVoBU7f3y29pqKW9KySMaci8CbL-65UQdzNbUN3Qb2PiVzufMztR2b6RnSRVHo4CaWNKIUausI-ibB1q0ZXWzFuj7n9aCWGtoRay_IljUww3L5EcQqNTMkuJ5CglBp_yA4Qk35WW4mHTS9R3_u2ggxG4wj_lC9tbSV4vbAHPsCknxoVTlPQUaETc9h17IkXET9ZmDi7lSBZI1qSAQ__uy9j92OaCoOmYbIKcV1ZBeFZvk5BG6w0u4734VmeaKgk-fDycxALP3OFS6_RFGgbrowzE0Nd3QC6EeveO8Z5AKHcyDRHMsoKYsTiUOQi4R1tohHK4KhLOcRtyyCNJhTFaDROxfv4qHXN8zaTWfUbVp72cLk3hfIZ8LvXKwhLb7krBanFMu40g9s1VFza1mhGqGUqfAqdyZ9Ldk-bm6XZ-fxrxjapu6a6KxJbYbYnNutlOdRw5xl1VzbBuK85YlvcFNVw2Jaka2za2hX32z7AxFwgcS9hJUmldS4MaBmGgDq0JUZMX828wMVn6-3SdODmmlTdFoYdKT5Mf7Olum-oRn52gaeVTv_XWoSfaLxuhvuky0bN1XqBXUJRLN2GPBDneceDepNvDRQ7HMZZeXAHyHQ93M44CdU4HI5jzmMVPfl-Fu_UBmCODU7BtD0aSf1osNp-MEETZLsNx8YbPzCav62R2203nvGcOPy8t4sYXra4MDdYIIo4so2EWWnF2-Vu8KKlrXYSN00NryR7MPKH39A3v8jzruC4AcUJ-9FZ6VfcDEq0wGLr3HghAYfK_Uf5mJxWEavXfHNhN29XTBJkdWGpMwpnI4dgjxDcD3n9GGmeJSH4w48zLimvF57S_j7Gziip4EYtZDDtz58CJxjx6DXJbwT0j-qtdlghmfz5hrh-7uNF1jCuh5MDNgj-dbMwkbKDR8gV8bzEVLIdvhIBSXdw8fh4WMGFXVjm5acGF20L0uB6ypLutlX51Q9fo-XCB17ReWvFz7jE824xUBRfSHHZbZefJMYQlT4wzZJ9JA_ea_LvbmsB6igDmjIlA4sjo_0c_nE7LAEgUGEx-CXd1X8n6UrO8FrmylNm7yMKeqBPzm78pPPbSBNEWkz6Kuu2-gEX6B4ggjSBgF1xHz49vxDzHgsQWmJF352qUkczRHXYad10g-GokxhMBUrlLzmQKjo9qpq5VQOx7mKGC3KDCTn6vDtYWJwvfZbbn_N5zcnT31crbij1mKlV2gsgOwCeVq2j9ROJA-CDMt15A-kXlHVZOjZBFTqvlVpOHUtpjUzDb4M6_t7rL6pOX4oznLnelMlCLHsav20e8KbNGZRp1Epf1qH3fUzTiSMZte14d60Z9O4cKgTi9ku0Cm2Ss_e_hgxzSI4xeT5fqgNhkrbw0b08hU05z6glYu4O3wGfnZAECu-_R17uMftHaERlhUrsJgqDPUJtJdVz3PZFX4BadUiDfFoDAkCIm-jEQEKyZ06hzmlEW2kxhKoM7sTnJdCYMegx1i5wApZ_kWZuo8JUT6pGiTEQ51moQobRasPRukNBVnBnJu-EeQOiV27J03qbMTabb6c60Y6yL-Zn_er8YG8CJB-BmPQ192A-1ekqxJskQMmzEUg93BsFC3fzc0PUbywrK3tulqeice183DW48HMa9xsP5Lyt7vMv12CzqJcBtbm377d4TCEq-T9SSkIWOOv_zVUYzCHjQutFhVs8WTWny4AtrhMl0Mm4ZJbFRygqGglORVXCtphEKgUvIL2nP-nla6R_WH-TdsHmjVg6iNDbu0Qv3e9jA6h4sOj5rhc8wPnWuO-MaGvyUxDtJyvt90yAqQiel8qbYTUqqc__830-Y2BkW-oWttKkUYBwMpg8zq8yrYQXcL65Qg1XA4GepdGzv8L6fp_3bAI4TyCHr7ptleyUfofe53SkMVEUEHeHOFKc79VQr7VCGrwHdrgmysQC-NTet8="}}
{"timestamp":"2025-09-22T13:27:57.467Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"Get-Content -Raw \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\"\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_kaxEDFLbFYQ6q2xnzm8JO5c6"}}
{"timestamp":"2025-09-22T13:27:57.467Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_kaxEDFLbFYQ6q2xnzm8JO5c6","output":"{\"output\":\"using System;\\nusing System.Collections.Generic;\\nusing System.Linq;\\nusing System.Threading.Tasks;\\nusing Google.OrTools.LinearSolver;\\nusing Microsoft.Extensions.Logging;\\nusing NPP.SmartSchedue.Api.Contracts.Domain.Work;\\nusing NPP.SmartSchedue.Api.Contracts.Domain.Personnel;\\nusing NPP.SmartSchedue.Api.Contracts.Services.Integration.Internal;\\nusing NPP.SmartSchedue.Api.Contracts.Services.Integration.Output;\\n\\nnamespace NPP.SmartSchedue.Api.Services.Integration.Algorithms\\n{\\n    /// <summary>\\n    /// 增强版线性规划引�?- 实现遗传算法中的所有复杂约�?\\n    /// 核心功能：三级约束体�?+ 多维度目标优�?+ 完整业务规则支持\\n    /// 设计理念：将遗传算法的启发式约束转换为严格的数学约束，实现精确求�?\\n    /// 技术架构：Google OR-Tools + 分层约束建模 + 自适应权重优化\\n    /// 业务价值：提供数学最优解，替代遗传算法的近似解，提升调度质量\\n    /// </summary>\\n    public class LinearProgrammingEngine\\n    {\\n        private readonly ILogger<LinearProgrammingEngine> _logger;\\n        private readonly ShiftRuleValidationEngine _shiftRuleEngine;\\n        \\n        // 求解器配�?- 增强版配置支持复杂约�?\\n        private const string SOLVER_TYPE = \\\"CBC_MIXED_INTEGER_PROGRAMMING\\\";\\n        private const double OPTIMALITY_TOLERANCE = 1e-6;\\n        private const int MAX_SOLVER_TIME_SECONDS = 600; // 增加�?0分钟支持复杂约束\\n        private const int MAX_CONSTRAINT_COUNT = 50000;   // 最大约束数量限�?\\n        \\n        // 约束权重配置 - 对应遗传算法的三级约束体�?\\n        private const double LEVEL1_CONSTRAINT_PENALTY = 1000000.0; // Level 1: 基础约束严厉惩罚\\n        private const double LEVEL2_CONSTRAINT_PENALTY = 100000.0;  // Level 2: 组合约束重度惩罚  \\n        private const double LEVEL3_CONSTRAINT_PENALTY = 10000.0;   // Level 3: 业务约束中度惩罚\\n        private const double FAIRNESS_REWARD_FACTOR = 1000.0;       // 公平性奖励系�?\\n\\n        public LinearProgrammingEngine(\\n            ILogger<LinearProgrammingEngine> logger,\\n            ShiftRuleValidationEngine shiftRuleEngine)\\n        {\\n            _logger = logger ?? throw new ArgumentNullException(nameof(logger));\\n            _shiftRuleEngine = shiftRuleEngine ?? throw new ArgumentNullException(nameof(shiftRuleEngine));\\n        }\\n\\n        /// <summary>\\n        /// 执行增强版线性规划优�?- 实现遗传算法等价的约束体�?\\n        /// 业务流程：构建决策变�?�?三级约束建模 �?多目标优�?�?精确求解 �?解析结果\\n        /// 核心创新：将启发式约束转换为线性约束，实现数学最优解\\n        /// </summary>\\n        public async Task<GlobalOptimizedSolution> OptimizeAsync(GlobalAllocationContext context)\\n        {\\n            var stopwatch = System.Diagnostics.Stopwatch.StartNew();\\n            \\n            try\\n            {\\n                _logger.LogDebug(\\\"🚀 启动增强版线性规划优�?- 任务数：{TaskCount}，人员数：{PersonnelCount}，预筛选缓存：{CacheSize}\\\", \\n                    context.Tasks.Count, context.AvailablePersonnel.Count, context.PrefilterResults.Count);\\n\\n                // 第一步：创建高性能求解�?\\n                using var solver = CreateAdvancedSolver();\\n\\n                // 第二步：构建决策变量矩阵 (x[i,j] = 1表示任务i分配给人员j)\\n                var decisionVariables = BuildDecisionVariables(solver, context);\\n                _logger.LogDebug(\\\"📊 决策变量构建完成 - 变量数量：{VariableCount}\\\", decisionVariables.Count);\\n\\n                // 第三步：构建辅助变量 (支持复杂约束建模)\\n                var auxiliaryVariables = BuildAuxiliaryVariables(solver, context, decisionVariables);\\n                _logger.LogDebug(\\\"🔧 辅助变量构建完成 - 辅助变量数量：{AuxCount}\\\", auxiliaryVariables.Count);\\n\\n                // 第四步：Level 1 基础约束 - 对应遗传算法的基础约束验证\\n                await AddLevel1BasicConstraints(solver, decisionVariables, auxiliaryVariables, context);\\n\\n                // 第五步：Level 2 组合约束 - 对应遗传算法的组合约束验�? \\n                await AddLevel2CombinationConstraints(solver, decisionVariables, auxiliaryVariables, context);\\n\\n                // 第六步：Level 3 业务约束 - 对应遗传算法的业务逻辑约束\\n                await AddLevel3BusinessConstraints(solver, decisionVariables, auxiliaryVariables, context);\\n\\n                // 第七步：公平性约�?- 对应遗传算法的负载均衡机�?\\n                AddFairnessConstraints(solver, decisionVariables, auxiliaryVariables, context);\\n\\n                // 第八步：设置多维度目标函�?- 对应遗传算法的适应度函�?\\n                SetEnhancedObjectiveFunction(solver, decisionVariables, auxiliaryVariables, context);\\n\\n                // 第九步：执行求解\\n                _logger.LogInformation(\\\"🔍 开始求解增强版线性规划模�?..\\\");\\n            \\n[... omitted 2156 of 2412 lines ...]\\n\\n                \\n                // 检查历史任务人员的分配\\n                if (context.PersonnelHistoryTasks.TryGetValue(personnelId, out var historyTask))\\n                {\\n                    var taskDate = task.WorkOrderDate.Date;\\n\\n                    if (historyTask.Any(m => m.WorkDate.Date == taskDate))\\n                    {\\n                        return true;\\n                    }\\n                }\\n                \\n                return false; // 人员可用\\n            }\\n            catch (Exception ex)\\n            {\\n                _logger.LogWarning(ex, \\\"⚠️ 检查人员不可用性异�?- 任务{TaskId}人员{PersonnelId}，默认为不可�?, \\n                    task.Id, personnelId);\\n                return true; // 异常情况下保守处理，标记为不可用\\n            }\\n        }\\n\\n        /// <summary>\\n        /// 【Ultra think方法】检查人员在指定任务时间是否不可用（异步版本�?\\n        /// 【扩展支持】：为未来集成更复杂的不可用性检查逻辑预留接口\\n        /// </summary>\\n        private async Task<bool> IsPersonnelUnavailableForTaskAsync(WorkOrderEntity task, long personnelId, GlobalAllocationContext context)\\n        {\\n            // 目前直接调用同步版本，保持异步接口以便未来扩�?\\n            await Task.CompletedTask;\\n            return IsPersonnelUnavailableForTask(task, personnelId, context);\\n        }\\n\\n        #endregion\\n    }\\n\\n    /// <summary>\\n    /// 人员任务矩阵 - 支持高效的关联查�?\\n    /// </summary>\\n    public class PersonnelTaskMatrix\\n    {\\n        public Dictionary<long, List<WorkOrderEntity>> PersonnelTaskMap { get; set; } = new();\\n        public Dictionary<long, List<GlobalPersonnelInfo>> TaskPersonnelMap { get; set; } = new();\\n    }\\n\\n    /// <summary>\\n    /// 时间窗口定义\\n    /// </summary>\\n    public class TimeWindow : IEquatable<TimeWindow>\\n    {\\n        public DateTime Date { get; set; }\\n        public long ShiftId { get; set; }\\n        public TimeSpan StartTime { get; set; }\\n\\n        public bool Equals(TimeWindow other)\\n        {\\n            if (other == null) return false;\\n            return Date.Date == other.Date.Date && \\n                   ShiftId == other.ShiftId && \\n                   StartTime == other.StartTime;\\n        }\\n\\n        public override bool Equals(object obj) => Equals(obj as TimeWindow);\\n        \\n        public override int GetHashCode() => HashCode.Combine(Date.Date, ShiftId, StartTime);\\n    }\\n\\n    /// <summary>\\n    /// 冲突严重程度枚举\\n    /// </summary>\\n    public enum ConflictSeverity\\n    {\\n        None = 0,        // 无冲�?\\n        Low = 1,         // 轻微冲突\\n        Medium = 2,      // 中等冲突\\n        High = 3,        // 严重冲突\\n        Critical = 4     // 关键冲突\\n    }\\n\\n    /// <summary>\\n    /// WorkOrderEntity扩展方法 - 为LinearProgrammingEngine提供辅助功能\\n    /// </summary>\\n    public static class WorkOrderEntityExtensions\\n    {\\n        /// <summary>\\n        /// 【深度实现】为验证目的克隆WorkOrderEntity\\n        /// 【业务思考】：在线性规划验证过程中，需要模拟分配的临时任务对象\\n        /// 【技术要点】：仅复制验证所需的关键字段，避免整体对象克隆的性能开销\\n        /// </summary>\\n        public static WorkOrderEntity CloneForValidation(this WorkOrderEntity original)\\n        {\\n            return new WorkOrderEntity\\n            {\\n                Id = original.Id,\\n                ProjectNumber = original.ProjectNumber,\\n                ProjectCategory = original.ProjectCategory,\\n                ShiftId = original.ShiftId,\\n                ShiftCode = original.ShiftCode,\\n                ShiftName = original.ShiftName,\\n                WorkOrderCode = original.WorkOrderCode,\\n                WorkOrderDate = original.WorkOrderDate,\\n                Priority = original.Priority,\\n                Urgency = original.Urgency,\\n                ComplexityLevel = original.ComplexityLevel,\\n                EstimatedHours = original.EstimatedHours,\\n                Status = original.Status,\\n                AssignedPersonnelId = original.AssignedPersonnelId, // 这个将被修改为模拟分配的人员ID\\n                // 关联对象也需要复�?\\n                ShiftEntity = original.ShiftEntity,\\n                ProcessEntity = original.ProcessEntity,\\n                WorkOrderFLPersonnels = original.WorkOrderFLPersonnels\\n            };\\n        }\\n    }\\n\\n    /// <summary>\\n    /// 解质量指�?\\n    /// </summary>\\n    public class SolutionQualityMetrics\\n    {\\n        public double TaskCompletenessRate { get; set; }\\n        public double TimeConflictRate { get; set; }\\n        public double LoadBalanceScore { get; set; }\\n        public double PersonnelUtilizationRate { get; set; }\\n        public double ConstraintSatisfactionRate { get; set; }\\n        public List<string> ViolationDetails { get; set; } = new();\\n    }\\n}\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.2}}"}}
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{"timestamp":"2025-09-22T13:28:06.065Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Preparing to analyze large engine file**"}}
{"timestamp":"2025-09-22T13:28:06.908Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":9475,"cached_input_tokens":5888,"output_tokens":714,"reasoning_output_tokens":576,"total_tokens":10189},"last_token_usage":{"input_tokens":6123,"cached_input_tokens":3456,"output_tokens":456,"reasoning_output_tokens":384,"total_tokens":6579},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:28:06.908Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Preparing to analyze large engine file**"}],"content":null,"encrypted_content":"gAAAAABo0U7n2SYQJbVyuL3RywQiaCPbM6QRF4LVCFe00Q2Pper-0VwBzay3w_dgxp4Hl_rUOT0PlrhHR1DQDg1ZJjjQNrhNNpaoFhtNSDWey8TUzgdT2SFriIKqsBUvB8tXlOwpEy3yi7CgyXBgbqoMB1Qb84xXJ0TLbzZp4Oq9Jvg-u2M86mwSMd_zs7Omt5Lufm1tsLMx22RFCyckpYNqsSMrsW6EL185eu0uswlS_yKqigWvalSstFAqIpfRCWnRiWm9bDmoitMtPzKUvmxgH72FpcHESaeplPnB9Y5Edtt4kLc2y9VSl-VmasgGyHhRmcnvQpu7I50iZHlDVsXAPvtTm8-wGKMeuO1yjWjk4yCBfefhXr1IaKhRYtG9skFC93BDlYvtqwEyb46-mEq4Uh_RmWkFCSpLMXAW3gsMkhgHn0X4qhW9Bo5ddUgNYmPxHlc_Yk2Z1sVygo8Eb2nYJLi5DjE9hYfMG-1xhKexDtQckcGS09MWC8ZD8dKOVUXDRtyff-o-biXiuT0G6LSJ_xfi7qMWtwb9C8skg5sjv3Zo9VeDTGjp51CdZ1RODStGYpoe-iAPT31rkSUa_E-kef96BGoBPRbut3HGt8-c9b2Os-WRmaZ3qPglf2Ji7-hQTtyc6c1-_ccWr2GVNADQCGaAIW-F2eJbNzeCie4Qjs2w6GuDC4lWVMuQ-mqATvH-Y_S1_IKOMxtdfjys-lNS6-UNj3UshyShQNFTh_7jSf64HPeu_F3RcXqtEOWOLGe3cWzwrTX95vrajDRGC2Kx6uW4o5I2jj1lXQShcHHl8lES5dYc63AmmbS-4lFB8MQdBI-0SLVFd8gTJDP97gxF54KBbnsT3oJxv0OULCnHt9pEa_biZhDYF5BBeAHH8DuZ57-zxz2hFCrbAXvsPem2xI0xI3Dt4X6Lpb12EkbI7GjNyi7J72x-1Bb9ddgkZH132RgPUY6lf7srZluOJ_PQ74IVAUM1OYVpFLyyvO96Vyy5Qg8p-KE6UAMBG3XXoc0wcE68G1xA1rgSvYz5a3K_D6nNBAWxxNmGYzIQIRRiuEoHwBqjJ1acWOWyo1MVsVjf5PfLSzruwFZEib1pVZ1w3G7hcJEEKxyssg5OWFDwal9n1GjtHTSf3QiceaBnNNfCKTjWiXNpIXLmPAZKL_QGAM1eLdfjxRVagnIA0Wnfgh5XSUlYacJ6EVXAWGYa-XcfBxjtZFlSSaH3ZNpdjzRXihs2Er0kOiiGZhgjEYBRRmaCpmPS9zqGPzu5_qLH7G6zdIQA8NRcYq3lD8_zytnPlPMQMsQk95iQlJ364MUnrEZjZt3FZcxvxhpaPJGEl9Cihf0c5fI71z7tAKRzbs_VjlzBuk7yS6Ix1ilZY_jW_9sHAQWhVadA46G45D_eteI0d9E57JrM7WM3C4qcP675w8ie0yeuI37fqXkOsl7OeGH2P0sdd3IJMGFE1_UwUgyGOeMQnAVcgxI1tDStGegfwdHYb8n2iHpmSMGD1C-oTcQRnZ0NbImVkmGwSS6TjuyPlbb40PSjPAp2rWVnvDupi5XiuyBORBz3fEyIwgYJrMThttMPBk-zxHH1NZahsRa36_vcG8TZJtnqu5XC_H6yK-fF5PuyXceYEv9p8hb_mL6Fs2Frhac8LpEfJV7aQQEgxC2DXAL9Y47sbpvXRw2v3ll34WW-LLIVg7U7Spb-e39BiA9BSSmsz-rZ0E4lM2qxHIQzXBKlH2zLDyzndDkasKnnEQ0HJEFunDl-za9qlPHHWpSJb3CbnQivAzPEz9pV5RXW7GjkbXwHJt06plhjqB40nigLmvkjK3PiEAWCEqy9yturSuIfb1eB0cjtuiUmZLeitkdbMvIsL00a_FmyKwBUuOShjM9KV0cTER5a18OUHUh5eTfOLkJ2Ay7xv3YP_Qof6MRquZH1t0AAUd8sDW0-npdBjrO-evhUJ5nk6y4SML4Sxym8wavi1UYR6QebcHIz19v-97CddfaLlyMpILUfEjKv_qs6Nm74giu78qRGZxhJVvJRnDHj-O4f5aFyJF9vUlAi0rq2OT7ShVpTwhmGPIQ6TC-fR2rlEvSsewPSn4cCqbbBqwvA5Cv11ATryBoFywNxY3n5AGzYEOtVsK5wwNOm1kZ7Ixdzap2hSdHhE4nCQW4Xv3t8o9hM0NgnfJE7ecka07cIZ4MgVupXVV0MBHa-1ge_cU9Ha1qOsx7Dx3H89zDgYNEA3so1Lm--r0puzl6RzIqVDPXCjuGx0vFqYE8i3T0rGDq3KkQ1CnESH2bigU_QNHOOnKN8JS8mRbneRuEI36l2j_IJ4tIsD2ub6qg21yzx9qbTnhw6yj-3zdGiWhC3a7g_5k2Kof-QOUXRmE6l4QXR5iPvSco8PfijSwcSyaO3GaCkLW80haiHP3SXSLyiyQpPGDPN1JY78MYsvi2UN-kqBh0nyRT3ADDHsRaiKe5uiFEKykwBoLsI3onwzy7xylUO0uYsHlsGqPq2nnSM7bVhOlCH3sTBNwjlbe62wCVHejVPsSUkAoQWL9dXsjE9CcG2OvzsM8iefSb-s8uPgRn7W530LpfkF8YU43XrTEihkaHK04avIINg6CUzRUiKYLmgfYrrfd0qabynf7Dkx48vm40XchfSQctpxo5HKmlzKuYyOiNH5o5ipL5ZWLYAz0vcfnw4uc3pyvwbrmeeVDUD0JPOnKA-9n8V980BlVhbj8EK1bwvaRAYGSV7skO_HsUQLzC7eHUThOKEZaDXwuEEq0WBt9ge7eB2MwVohecCs_2ObGF0VOrjLS1qmMfBgqEtQYWvojcrjubz8OFdjPDW4HY_bOgBZD_gXYG-5Ikpz9tvHukcPNX7aiKesLPw72zLsxB_DkGxVMYItLR5ME2y0lGK_QAg1ImzqkE6RYZtpO_cTtFyZqjNsRkCY6evnPyj8-t5Kpfgt8odSQ3Y2FfQ_eJjekoLwgjix_O96SE0Np7H6tSAMCSRRmp1aqEQ8AGpSSukOua02t_yPxN_-ILZrsP76CyQEVkhCdS4J6ShV8zyxm74Pvprm0ln-gb9Q7lt0qsCkdWZFCQ-fo88V34GaxOl28PKsh-CrZOppphOjNLArGH1r7VrMl8AY55byXKVzwXOWVHNigHylr-yQn1vMTKn5nZlKcDtLoKfo9a18BldXOF78A_AmLWqfk9m0_fzupbzkW81am6Hh3CfNhoA2sDsefBAUwbuEpqXPacUu9M9bcsIB2mAeovjPICJRA6q9pUtWI_yDRSeLi6HyW9EKUkPFzZ3X_yEkb7DVscnKxs6R4WG5Wm78Jg0XfPWYsh6paYnvCdfrX0BlRvd3sh6LF5dgkxcuFXbHJRGboyWI4npJRpokFnSoIfivWA="}}
{"timestamp":"2025-09-22T13:28:06.908Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"Get-Content \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\" | Select-Object -First 400\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_R3Qeij20Pbiqky4HCNHNwrWP"}}
{"timestamp":"2025-09-22T13:28:06.908Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_R3Qeij20Pbiqky4HCNHNwrWP","output":"{\"output\":\"using System;\\nusing System.Collections.Generic;\\nusing System.Linq;\\nusing System.Threading.Tasks;\\nusing Google.OrTools.LinearSolver;\\nusing Microsoft.Extensions.Logging;\\nusing NPP.SmartSchedue.Api.Contracts.Domain.Work;\\nusing NPP.SmartSchedue.Api.Contracts.Domain.Personnel;\\nusing NPP.SmartSchedue.Api.Contracts.Services.Integration.Internal;\\nusing NPP.SmartSchedue.Api.Contracts.Services.Integration.Output;\\n\\nnamespace NPP.SmartSchedue.Api.Services.Integration.Algorithms\\n{\\n    /// <summary>\\n    /// 增强版线性规划引�?- 实现遗传算法中的所有复杂约�?\\n    /// 核心功能：三级约束体�?+ 多维度目标优�?+ 完整业务规则支持\\n    /// 设计理念：将遗传算法的启发式约束转换为严格的数学约束，实现精确求�?\\n    /// 技术架构：Google OR-Tools + 分层约束建模 + 自适应权重优化\\n    /// 业务价值：提供数学最优解，替代遗传算法的近似解，提升调度质量\\n    /// </summary>\\n    public class LinearProgrammingEngine\\n    {\\n        private readonly ILogger<LinearProgrammingEngine> _logger;\\n        private readonly ShiftRuleValidationEngine _shiftRuleEngine;\\n        \\n        // 求解器配�?- 增强版配置支持复杂约�?\\n        private const string SOLVER_TYPE = \\\"CBC_MIXED_INTEGER_PROGRAMMING\\\";\\n        private const double OPTIMALITY_TOLERANCE = 1e-6;\\n        private const int MAX_SOLVER_TIME_SECONDS = 600; // 增加�?0分钟支持复杂约束\\n        private const int MAX_CONSTRAINT_COUNT = 50000;   // 最大约束数量限�?\\n        \\n        // 约束权重配置 - 对应遗传算法的三级约束体�?\\n        private const double LEVEL1_CONSTRAINT_PENALTY = 1000000.0; // Level 1: 基础约束严厉惩罚\\n        private const double LEVEL2_CONSTRAINT_PENALTY = 100000.0;  // Level 2: 组合约束重度惩罚  \\n        private const double LEVEL3_CONSTRAINT_PENALTY = 10000.0;   // Level 3: 业务约束中度惩罚\\n        private const double FAIRNESS_REWARD_FACTOR = 1000.0;       // 公平性奖励系�?\\n\\n        public LinearProgrammingEngine(\\n            ILogger<LinearProgrammingEngine> logger,\\n            ShiftRuleValidationEngine shiftRuleEngine)\\n        {\\n            _logger = logger ?? throw new ArgumentNullException(nameof(logger));\\n            _shiftRuleEngine = shiftRuleEngine ?? throw new ArgumentNullException(nameof(shiftRuleEngine));\\n        }\\n\\n        /// <summary>\\n        /// 执行增强版线性规划优�?- 实现遗传算法等价的约束体�?\\n        /// 业务流程：构建决策变�?�?三级约束建模 �?多目标优�?�?精确求解 �?解析结果\\n        /// 核心创新：将启发式约束转换为线性约束，实现数学最优解\\n        /// </summary>\\n        public async Task<GlobalOptimizedSolution> OptimizeAsync(GlobalAllocationContext context)\\n        {\\n            var stopwatch = System.Diagnostics.Stopwatch.StartNew();\\n            \\n            try\\n            {\\n                _logger.LogDebug(\\\"🚀 启动增强版线性规划优�?- 任务数：{TaskCount}，人员数：{PersonnelCount}，预筛选缓存：{CacheSize}\\\", \\n                    context.Tasks.Count, context.AvailablePersonnel.Count, context.PrefilterResults.Count);\\n\\n                // 第一步：创建高性能求解�?\\n                using var solver = CreateAdvancedSolver();\\n\\n                // 第二步：构建决策变量矩阵 (x[i,j] = 1表示任务i分配给人员j)\\n                var decisionVariables = BuildDecisionVariables(solver, context);\\n                _logger.LogDebug(\\\"📊 决策变量构建完成 - 变量数量：{VariableCount}\\\", decisionVariables.Count);\\n\\n                // 第三步：构建辅助变量 (支持复杂约束建模)\\n                var auxiliaryVariables = BuildAuxiliaryVariables(solver, context, decisionVariables);\\n                _logger.LogDebug(\\\"🔧 辅助变量构建完成 - 辅助变量数量：{AuxCount}\\\", auxiliaryVariables.Count);\\n\\n                // 第四步：Level 1 基础约束 - 对应遗传算法的基础约束验证\\n                await AddLevel1BasicConstraints(solver, decisionVariables, auxiliaryVariables, context);\\n\\n                // 第五步：Level 2 组合约束 - 对应遗传算法的组合约束验�? \\n                await AddLevel2CombinationConstraints(solver, decisionVariables, auxiliaryVariables, context);\\n\\n                // 第六步：Level 3 业务约束 - 对应遗传算法的业务逻辑约束\\n                await AddLevel3BusinessConstraints(solver, decisionVariables, auxiliaryVariables, context);\\n\\n                // 第七步：公平性约�?- 对应遗传算法的负载均衡机�?\\n                AddFairnessConstraints(solver, decisionVariables, auxiliaryVariables, context);\\n\\n                // 第八步：设置多维度目标函�?- 对应遗传算法的适应度函�?\\n                SetEnhancedObjectiveFunction(solver, decisionVariables, auxiliaryVariables, context);\\n\\n                // 第九步：执行求解\\n                _logger.LogInformation(\\\"🔍 开始求解增强版线性规划模�?..\\\");\\n            \\n[... omitted 144 of 400 lines ...]\\n\\n    }\\n\\n            // 基础约束2：基本时间冲突约�?- 同一人员不能在同一时间段执行多个任�?\\n            // 这里使用线性约束替代遗传算法中的CalculateBasicTimeConflictScore逻辑\\n            foreach (var personnel in context.AvailablePersonnel)\\n            {\\n                // 按时间段分组检查冲�?\\n                var timeGroups = context.Tasks.GroupBy(t => new { Date = t.WorkOrderDate.Date });\\n                \\n                foreach (var timeGroup in timeGroups)\\n                {\\n                    var timeSlotTasks = timeGroup.ToList();\\n                    if (timeSlotTasks.Count > 1) // 同一时间段有多个任务才需要约�?\\n                    {\\n                        var timeSlotVariables = timeSlotTasks\\n                            .Where(task => decisionVars.ContainsKey((task.Id, personnel.Id)))\\n                            .Select(task => decisionVars[(task.Id, personnel.Id)])\\n                            .ToList();\\n\\n                        if (timeSlotVariables.Count > 1)\\n                        {\\n                            // 约束：同一人员在同一时间段最多执�?个任�?\\n                            var constraint = solver.MakeConstraint(0, 1, \\n                                $\\\"time_conflict_{personnel.Id}_{timeGroup.Key.Date:yyyyMMdd}\\\");\\n                            \\n                            foreach (var variable in timeSlotVariables)\\n                            {\\n                                constraint.SetCoefficient(variable, 1);\\n                            }\\n                            constraintCount++;\\n\\n                            // 连接辅助变量（用于目标函数惩罚）\\n                            var conflictVarKey = $\\\"conflict_{personnel.Id}_{timeGroup.Key.Date:yyyyMMdd}\\\";\\n                            if (auxiliaryVars.ContainsKey(conflictVarKey))\\n                            {\\n                                // 如果分配了多个任务，冲突变量=1\\n                                var conflictConstraint = solver.MakeConstraint(0, double.PositiveInfinity, \\n                                    $\\\"conflict_indicator_{personnel.Id}_{timeGroup.Key.Date:yyyyMMdd}\\\");\\n                                \\n                                foreach (var variable in timeSlotVariables)\\n                                {\\n                                    conflictConstraint.SetCoefficient(variable, 1);\\n                                }\\n                                conflictConstraint.SetCoefficient(auxiliaryVars[conflictVarKey], -timeSlotVariables.Count + 1);\\n                                constraintCount++;\\n                            }\\n                        }\\n                    }\\n                }\\n            }\\n\\n            // 基础约束3：工作负载计算约�?- 连接决策变量与辅助变�?\\n            foreach (var personnel in context.AvailablePersonnel)\\n            {\\n                var personnelTasks = decisionVars.Where(v => v.Key.PersonnelId == personnel.Id).ToList();\\n                if (personnelTasks.Any() && auxiliaryVars.ContainsKey($\\\"workload_{personnel.Id}\\\"))\\n                {\\n                    var constraint = solver.MakeConstraint(0, 0, $\\\"workload_calc_{personnel.Id}\\\");\\n                    \\n                    foreach (var kvp in personnelTasks)\\n                    {\\n                        constraint.SetCoefficient(kvp.Value, 1);\\n                    }\\n                    constraint.SetCoefficient(auxiliaryVars[$\\\"workload_{personnel.Id}\\\"], -1);\\n                    constraintCount++;\\n                }\\n            }\\n\\n            _logger.LogDebug(\\\"�?Level 1基础约束添加完成 - 约束数量：{ConstraintCount}\\\", constraintCount);\\n        }\\n\\n        #endregion\\n\\n        #region Level 2 组合约束 - 对应遗传算法组合约束验证\\n\\n        /// <summary>\\n        /// 添加Level 2组合约束 - 对应遗传算法的ExecuteLevel2CombinationConstraintValidation\\n        /// 约束内容：动态班次规则、跨任务资源竞争约束\\n        /// 约束特点：基于任务组合的动态验证，违反时重度惩�?\\n        /// </summary>\\n        private async Task AddLevel2CombinationConstraints(\\n            Solver solver,\\n            Dictionary<(long TaskId, long PersonnelId), Variable> decisionVars,\\n            Dictionary<string, Variable> auxiliaryVars,\\n            GlobalAllocationContext context)\\n        {\\n            var constraintCount = 0;\\n            \\n            _logger.LogDebug(\\\"🔄 开始添加Level 2组合约束...\\\");\\n\\n            // 组合约束1：动态班次规则约�?- 对应CalculateDynamicShiftRuleScore\\n            //constraintCount += await AddDynamicShiftRuleConstraints(solver, decisionVars, auxiliaryVars, context);\\n            \\n            // 组合约束3：人员日工作量限制约�?\\n            //constraintCount += AddDailyWorkloadConstraints(solver, decisionVars, auxiliaryVars, context);\\n\\n            _logger.LogDebug(\\\"�?Level 2组合约束添加完成 - 约束数量：{ConstraintCount}\\\", constraintCount);\\n        }\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.4}}"}}
{"timestamp":"2025-09-22T13:28:06.908Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:28:09.877Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Planning deeper code inspection**"}}
{"timestamp":"2025-09-22T13:28:10.602Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":18471,"cached_input_tokens":12416,"output_tokens":848,"reasoning_output_tokens":640,"total_tokens":19319},"last_token_usage":{"input_tokens":8996,"cached_input_tokens":6528,"output_tokens":134,"reasoning_output_tokens":64,"total_tokens":9130},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:28:10.602Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Planning deeper code inspection**"}],"content":null,"encrypted_content":"gAAAAABo0U7q_RQjvO4JW4_6dW5KbeNd68D6CFoLk6dCk1RZzfAg26s5ytMKfgZGr0oizr7uAVcX-JMg9BeBxbEAIYZ-CH_eR8NobDbS646-llzPabTqYLaJA3RBGB3T3gSa1DfOohmVVGapREHz9HZABdE4Y3lLhnqAfVefIFfyNOf46uphhf_j38UtJ7BeHJXBFywlL1pluabstqr5FjuB3DEuM7YAojtIFM0NqKMSy2pWMTUbSBebPPZecYQCOXtT5Kiw_RtNXsHAjympI0qi3ZfE72PhFGuR2NG5UDoPQibP9dNkB-EqXJsZ2C2rkWuZwpdvjFyBxrMH__IbfXMURyhfyi9yeynRyCoi7uTBSWr8bmipHBceyK5Utoya6IINHftj0aYooFN0e33pi9--dJoMc5IqmSxRGFOl1yb4_IFwMCDLvzisYyV-6HvK1naF9h6sWtOTzDLsEytudZaodRH_nBd_kU9OvaIMg5PeOgxN68xASXjLA-cYbUGr4t9ztgsAK3DM2No--pwnaq6erjUy-Ex6d3nclzotpfZ5Lrg0M_v-tW9PXOttvnL5r5cMZtTR5uNnTDjoRKjHlpd-DwL_LOvhjNejxji9kURyXPbgrEJtmQsJTG8mhAJkG5CP-FHY9zDKc-n6eXlm6r1VIOHJVSx80uLpT9wfjstTwCl6YZp2iBbFqBR43g1PblpJlLoIWtNmZqRu6dOxwUQTmsK2gHJadZr5th0k2d1YYs7GoxuP2xuwu2VM2nBnTrN2eJY-ahyEcicKGzRwAwTiQEYtwS4a_QXUGWvTzIJnOnjp6slzNaGjucoHGj2ACRFpzuOoiVh0gE4hVSS0QbGe50413JbnJGWWUZaSBwXOnodwyiAwTxHjUNzo-mtG5Wq9QQsunVi4-unYtfaVBY78mXNVayPzNHgZ0SoM0D54J8uDPzmPQb3EOBlP9ONslm8mte7HLd3mWDWQtwTgmJyHPw-7Cvp4G5iTEBxSbjtOkiGaEAK3luHa6o3_7cno5LH649xEp7BQAPttPHr5r_moxig5n_MA_DLxrDj7e-Mf8bSQY61Sq-4I93f03h6Z9hyXzonKc7ccS8o3nPIa0caDq_AJ5ZcTewx3cAch_1ph7tqLC14wRfaRuaNzXg_ZN94LXn4OW-Yy-Qf3SXnfG_M-xC3wAwnDed-6eBC_O0HE04uiWf6wzXoj8hpjNHAVSlPpdtsgcQHA5YAPrp5ZVwZPr3LN2v1K9BmZaBmwcohFNG9wJIlC9HaVy2U5BokpAHjFbNzSh3ei01jeZnUNfa8-wnb6GfAU0hpY-Y6Fu5NY4kNlpYWs7erQZUo430ir4SgO0uLIOwWFoBh6Aw-_BHau6mmkepUo-wshWEN-DYU2z6qEBqdz1MkEPIEl5bFoJG7uWE2N9WbKFwas2VLvP9NmfKufVt6Mrf4dctU6C1wlUer-GWDARIz6FYR66Cxq1gBMDmJR6N39xQzVGWtR5RatMGdGNw4MwbSZpy5poCdYql1EHHB49nt-wHbx43GGDQRBIxrr7Of2"}}
{"timestamp":"2025-09-22T13:28:10.602Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"rg --line-number \\\"BuildDecisionVariables\\\" \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\"\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_8GJR8sZltsuL7FXh8XDupCrB"}}
{"timestamp":"2025-09-22T13:28:10.603Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_8GJR8sZltsuL7FXh8XDupCrB","output":"{\"output\":\"64:                var decisionVariables = BuildDecisionVariables(solver, context);\\r\\n141:        private Dictionary<(long TaskId, long PersonnelId), Variable> BuildDecisionVariables(\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.2}}"}}
{"timestamp":"2025-09-22T13:28:10.603Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:28:21.075Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Retrieving specific lines from file**"}}
{"timestamp":"2025-09-22T13:28:21.978Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":27705,"cached_input_tokens":21504,"output_tokens":1116,"reasoning_output_tokens":832,"total_tokens":28821},"last_token_usage":{"input_tokens":9234,"cached_input_tokens":9088,"output_tokens":268,"reasoning_output_tokens":192,"total_tokens":9502},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:28:21.978Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Retrieving specific lines from file**"}],"content":null,"encrypted_content":"gAAAAABo0U7273hLE1wKHteWaKdRP44FIxuNOWWPTusjsNgcOgWjXDPlx7EJpgs20loYO1UwQjmz51KuoOFeZPX2esKSjwTbFiBhv7F6ldBaHBDPlDXlwh2IW5XjHfFljCx6pExNv7XswVW3c42Mdo6fGxkN7u2dKVEKT7GSJ4j8R6qTMouBZXYKQUfm9ntOAYwHzZmJrygf3l7Q3ficCid8L8mAR9uoSOrbYWo7G56F7dRr3oTExVTzhBUcEV5lW-JphkkOV5MGyw9LJIfd4n0QadSwgKhtq1IxlZTk8KWchiOV1b8T3KxjvGlSNQVaJUyn6pjk509KQaThv1Zb6FtnGv2BG5RDGa0DM1xCOixEs6TL75D968pvIzLwJeAePiRD_tOPXFKeM4QTCf5LohXmVKEtvFlqlEZsRCwDCkxaevmsnydnSwjHI_aXjqwteZgJBbdptDDVLNKNCmJbUt4TYwZRaWrrLHN2KrZwbkUvenMcbU0SIUz-ouFBXSsTUJxvD6s-hTPIyMIU_co6bL_HqIWDJzVNivhADmWXFfv3k9mFlc6vXp2_h_59Sf6hpl23_eIbmMR-OwA3Qm_z_Puix79UmZxboFlVhym2PpT_j6ZBlJUWLvIowivysJmReL4LCUOmryQMEk0HL2peuIwby1fB868LfYalIaOzyvdjhIVqhaZ0gcqGt_reU6kSPDRHXyXX_mydEsUjPSrhXbd4f8YheVoYsGVRJYq-oEm12F4m07rH6ALnJErLPxL6L2GeBaYLU_zZbFZcsUby5m9zZwaPV7RG-YCFULunepGlzQjAO8SDnZsTBLy8JUKkG2sN6rbt36VLJrqOsPAf2pbsW_Ekg64QesbnPKR_o6YTazS4_Fsb_Uz5gNadM462Ky7VRguqQo5ajkohPnoduvMeqRapCnbn_Gy1jhtZ10emoswR17ngatHKfraIwPP-t_RTh6vEmh6HwubG50F6M6PhhgGXESLSQLijwZIRz49jI75zgSY5LzBdVcFXruJPvAl_LUJ1sJJUSn7TJ3y-qZ5WbN7x4Vo6LciIM2Lw2KGbHzdSHlSNQDow0BQQ5EHjeduwcntkUDEzOsqGJ3gAkYz7R_RtVxYzpHOe_u_kPV8InEJw2oNB4AGD0Ebw6JWzko3f9pitHrHmNKR-KKiBMybKcl-fTxTActSQMmJ9NYIiWp8qDdzrTPGXR_Jxt8wwyzla6ZHk2qB2Ym3C5kj_WAEE5_wAOctg0fu-RjtgkqaX5tcx7sg0M7O44tiOS6W9worMG8-wHDhelK8rNVk7aMuGUQUm6IT2Blj5lSV-gZ0_Oo0vpW-6fl1NLTmv51-2J2XtTduOxdyCUYF2xIwgN0xIJxEEOx6YDCKqnbaAj2FYFgF8pluh-0m9gUg9_oW1YYYXFtOLzsS8QqoXaB7y9XXm2PmIlelI2Jea-7wGx35gwBKnjU3YgBjneEW07eFf_yZSxFVDpcAhUc4gwiBv6gf03PaYXIFsrwXD6DNcb3IjZox6KJnKmqCUO5s23qYObghM7RpLg3wqUJm3LnNV0NaMSWpoO8GIVcpPgLal7WAD6O4rx4baRsOZGpKSkqktZ9XDFK7VI4XapOPmA8vydOGC27vjL2VpxFGwbtb7TKqkl0u_e7YGNpQ_uZUf0zUugE7LGig6_eY0JEXpLSe_VA1bdh-F7MdDJxFypxP4MFRLzLbCWGSDjtCQbVf2DCKo678m7qYeRQtD9yUgzzIlnhccnS_pgOB5c60vry8RxDYMd1_rEPxMjdzarGEuSAnLqRyzsipJVPJI"}}
{"timestamp":"2025-09-22T13:28:21.978Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"Get-Content \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\" | Select-Object -Skip 120 -First 140\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_R0RPQ7wYxvZMy6dF2ASLYiHD"}}
{"timestamp":"2025-09-22T13:28:21.978Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_R0RPQ7wYxvZMy6dF2ASLYiHD","output":"{\"output\":\"            solver.SetTimeLimit(MAX_SOLVER_TIME_SECONDS * 1000);\\r\\n            \\r\\n            // 设置优化参数\\r\\n            solver.SetSolverSpecificParametersAsString(\\r\\n                \\\"cuts=1 \\\" +           // 启用割平�?\\r\\n                \\\"heuristics=1 \\\" +     // 启用启发式算�?\\r\\n                \\\"presolve=1 \\\" +       // 启用预处�?\\r\\n                \\\"threads=0\\\"           // 使用所有可用线�?\\r\\n            );\\r\\n\\r\\n            _logger.LogInformation(\\\"🔧 高性能求解器创建完成，配置：时间限制{TimeLimit}s，多线程支持\\\", MAX_SOLVER_TIME_SECONDS);\\r\\n            return solver;\\r\\n        }\\r\\n\\r\\n        /// <summary>\\r\\n        /// 【Ultra think增强】构建决策变�?- 集成人员班次不可用性的智能变量生成\\r\\n        /// 【核心优化】：在变量创建阶段就排除不可用组合，大幅提升求解效率\\r\\n        /// 【三层优化】：预筛选结�?+ 不可用性检�?+ 评分阈值，实现精确的变量裁�?\\r\\n        /// 【性能提升】：预计减少20-40%的决策变量数量，显著提升求解速度\\r\\n        /// </summary>\\r\\n        private Dictionary<(long TaskId, long PersonnelId), Variable> BuildDecisionVariables(\\r\\n            Solver solver, GlobalAllocationContext context)\\r\\n        {\\r\\n            var variables = new Dictionary<(long TaskId, long PersonnelId), Variable>();\\r\\n            var createdCount = 0;\\r\\n            var skippedCount = 0;\\r\\n            var unavailabilitySkippedCount = 0;\\r\\n            \\r\\n            foreach (var task in context.Tasks)\\r\\n            {\\r\\n                foreach (var personnel in context.AvailablePersonnel)\\r\\n                {\\r\\n                    var prefilterKey = $\\\"{task.Id}_{personnel.Id}\\\";\\r\\n                    \\r\\n                    // 【Ultra think优化1】首先检查人员班次不可用�?- 硬排�?\\r\\n                    if (IsPersonnelUnavailableForTask(task, personnel.Id, context))\\r\\n                    {\\r\\n                        unavailabilitySkippedCount++;\\r\\n                        skippedCount++;\\r\\n                        _logger.LogDebug(\\\"🚫 跳过不可用组�?- 任务{TaskId}人员{PersonnelId}在{Date}班次{ShiftId}不可�?, \\r\\n                            task.Id, personnel.Id, task.WorkOrderDate.ToString(\\\"yyyy-MM-dd\\\"), task.ShiftId);\\r\\n                        continue;\\r\\n                    }\\r\\n                    \\r\\n                    // 【Ultra think优化2】基于预筛选结果的智能决策\\r\\n                    if (context.PrefilterResults.TryGetValue(prefilterKey, out var prefilterResult))\\r\\n                    {\\r\\n                        // 对于评分较高的分配，即使标记为不可行也创建变量（可能是保守评估）\\r\\n                        if (prefilterResult.IsFeasible || prefilterResult.PrefilterScore > 30.0)\\r\\n                        {\\r\\n                            var variableName = $\\\"x_{task.Id}_{personnel.Id}\\\";\\r\\n                            var variable = solver.MakeBoolVar(variableName);\\r\\n                            variables[(task.Id, personnel.Id)] = variable;\\r\\n                            createdCount++;\\r\\n                        }\\r\\n                        else\\r\\n                        {\\r\\n                            skippedCount++;\\r\\n                        }\\r\\n                    }\\r\\n                    else\\r\\n                    {\\r\\n                        // 【Ultra think优化3】无预筛选数据时的保守策�?\\r\\n                        // 即使无预筛选数据，但已通过不可用性检查，仍创建变�?\\r\\n                        var variableName = $\\\"x_{task.Id}_{personnel.Id}\\\";\\r\\n                        var variable = solver.MakeBoolVar(variableName);\\r\\n                        variables[(task.Id, personnel.Id)] = variable;\\r\\n                        createdCount++;\\r\\n                    }\\r\\n                }\\r\\n            }\\r\\n\\r\\n            _logger.LogDebug(\\\"📊 【增强版】决策变量构建统�?- 创建：{Created}个，跳过：{Skipped}个（不可用性：{UnavailabilitySkipped}），变量密度：{Density:P2}，不可用性优化率：{UnavailabilityRate:P2}\\\", \\r\\n                createdCount, skippedCount, unavailabilitySkippedCount, \\r\\n                (double)createdCount / (createdCount + skippedCount),\\r\\n                (double)unavailabilitySkippedCount / (createdCount + skippedCount));\\r\\n\\r\\n            return variables;\\r\\n        }\\r\\n\\r\\n        /// <summary>\\r\\n        /// 构建辅助变量 - 支持复杂约束的线性化建模\\r\\n        /// 包含：负载均衡变量、时间冲突指示变量、班次规则违规变量等\\r\\n        /// </summary>\\r\\n        private Dictionary<string, Variable> BuildAuxiliaryVariables(\\r\\n            Solver solver, GlobalAllocationContext context, \\r\\n            Dictionary<(long TaskId, long PersonnelId), Variable> decisionVariables)\\r\\n        {\\r\\n            var auxiliaryVars = new Dictionary<string, Variable>();\\r\\n\\r\\n            // 1. 人员工作负载变量 (连续变量，表示每个人员的任务数量)\\r\\n            foreach (var personnel in context.AvailablePersonnel)\\r\\n            {\\r\\n                var workloadVar = solver.MakeIntVar(0, context.Tasks.Count, $\\\"workload_{personnel.Id}\\\");\\r\\n                auxiliaryVars[$\\\"workload_{personnel.Id}\\\"] = workloadVar;\\r\\n            }\\r\\n\\r\\n            // 2. 负载均衡偏差变量 (支持公平性目标建�?\\r\\n            var avgWorkload = (double)context.Tasks.Count / context.AvailablePersonnel.Count;\\r\\n            foreach (var personnel in context.AvailablePersonnel)\\r\\n            {\\r\\n                // 正偏差变�?(超出平均负载的部�?\\r\\n                var posDeviationVar = solver.MakeNumVar(0, context.Tasks.Count, $\\\"pos_dev_{personnel.Id}\\\");\\r\\n                auxiliaryVars[$\\\"pos_dev_{personnel.Id}\\\"] = posDeviationVar;\\r\\n                \\r\\n                // 负偏差变�?(低于平均负载的部�?\\r\\n                var negDeviationVar = solver.MakeNumVar(0, avgWorkload, $\\\"neg_dev_{personnel.Id}\\\");\\r\\n                auxiliaryVars[$\\\"neg_dev_{personnel.Id}\\\"] = negDeviationVar;\\r\\n            }\\r\\n\\r\\n            // 3. 时间冲突指示变量 (二进制变量，标识是否存在时间冲突)\\r\\n            var timeSlots = context.Tasks.Select(t => new { Date = t.WorkOrderDate.Date })\\r\\n                                         .Distinct().ToList();\\r\\n            \\r\\n            foreach (var personnel in context.AvailablePersonnel)\\r\\n            {\\r\\n                foreach (var timeSlot in timeSlots)\\r\\n                {\\r\\n                    var conflictVar = solver.MakeBoolVar($\\\"conflict_{personnel.Id}_{timeSlot.Date:yyyyMMdd}\\\");\\r\\n                    auxiliaryVars[$\\\"conflict_{personnel.Id}_{timeSlot.Date:yyyyMMdd}\\\"] = conflictVar;\\r\\n                }\\r\\n            }\\r\\n\\r\\n            /*// 4. 班次规则违规变量 (支持复杂班次规则的线性化)\\r\\n            foreach (var personnel in context.AvailablePersonnel)\\r\\n            {\\r\\n                // 二班/三班后休息规则违规变�?\\r\\n                var shiftRuleViolationVar = solver.MakeIntVar(0, context.Tasks.Count, $\\\"shift_violation_{personnel.Id}\\\");\\r\\n                auxiliaryVars[$\\\"shift_violation_{personnel.Id}\\\"] = shiftRuleViolationVar;\\r\\n            }\\r\\n\\r\\n            // 5. FL优先级违规变�?(Level 3业务约束支持)\\r\\n            foreach (var task in context.Tasks)\\r\\n            {\\r\\n                var flViolationVar = solver.MakeBoolVar($\\\"fl_violation_{task.Id}\\\");\\r\\n                auxiliaryVars[$\\\"fl_violation_{task.Id}\\\"] = flViolationVar;\\r\\n            }*/\\r\\n\\r\\n            _logger.LogDebug(\\\"🔧 辅助变量构建完成 - 总数：{AuxVarCount}（工作负载：{WorkloadCount}，冲突指示：{ConflictCount}，班次违规：{ShiftCount}，FL违规：{FLCount}�?, \\r\\n                auxiliaryVars.Count,\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.3}}"}}
{"timestamp":"2025-09-22T13:28:21.978Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:28:23.543Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Continuing method review**"}}
{"timestamp":"2025-09-22T13:28:24.527Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":39137,"cached_input_tokens":30848,"output_tokens":1192,"reasoning_output_tokens":832,"total_tokens":40329},"last_token_usage":{"input_tokens":11432,"cached_input_tokens":9344,"output_tokens":76,"reasoning_output_tokens":0,"total_tokens":11508},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:28:24.527Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Continuing method review**"}],"content":null,"encrypted_content":"gAAAAABo0U74pIXmGpaa8JpaCO5ft0c_F7lCzZ94CvqLZ39SIcghyB77q3cfvEyJurUF4Q145QLoFniFTUECoWnWvMPxm0XIi60BbyCnTQXLhddSJ91Djf47LOxR47pst4uOrAOCkXsi4bbt4uwbDFliU61xnVcOBKkjpUm1Kmb9OFN8eRG48E1pYatPUm_wnJgGdTQ0rVphJXFt5HaEJRSgeTTZ_cKbADyl-TNRUFebnwGoZDSOz_w7p2SseA-cXs0S53pzqEmIS-S-6hBRmDIRkJ2hZGodVqGQqu7zoRlFIvK22338FazbJMvGKmvL1_9SACcLr16Ctrq14zzfZoLi3P7c98WabMDGnGb2xK1pPZHnPBqYczTY2apYmUwD4W8ZKDjP-6Pay_EAiixRyz2val9RuGjuM6jSsXe4Fz5EYCB4NIBnwHPNTdaf-40M1kNR64uLIuVrN_2UWlCzLbvoh80P3S03UE_To8DhUUIYdGMzWaaltXTBQoXSdH3Mp-SFwk6xGey93dB9kKA420x7Glqc_fDtSF3RuImsgTtHmzq5PbGBznJ6hxAqJXC1kcm9XgLjlFCsnyqMg3RPS4HDP-rFM4Qk7hYAkTHAm1JO0fpNscCOmetZEiLc9JxtqCUKrbtuwGhl979CXgFArPtxCxEQG52Rt_V6QLspB3dlFihGb3FrzQZBOxPsUSqfmKbjJE3ASvNjMds_qosrvS-kSVT6P8GeNDqKH0O4RSvq0DQNgjR5NF0ZTQQxZZPV8W6yjcpkaRJ6w34NYm6XosazA__zG0C0p81gVjLvfkbzoDGcRuI98fz0RwucV0NwPv_brqfqhGM5uDyNddgpTV78c7aqBW3FHA-zFANkV2DiRF36hEX3T8jOoigpYsgjiBghPGGQVuvj7kpZYLwDQ-c58t1jJT8IL_OEfHnOG-5DYOpAbpfoFeY="}}
{"timestamp":"2025-09-22T13:28:24.527Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"Get-Content \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\" | Select-Object -Skip 260 -First 120\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_fuvRlC3bPfpQKGMScABEoI8S"}}
{"timestamp":"2025-09-22T13:28:24.527Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_fuvRlC3bPfpQKGMScABEoI8S","output":"{\"output\":\"                context.Tasks.Count / context.AvailablePersonnel.Count,\\r\\n                context.AvailablePersonnel.Count * timeSlots.Count,\\r\\n                context.AvailablePersonnel.Count,\\r\\n                context.Tasks.Count);\\r\\n\\r\\n            return auxiliaryVars;\\r\\n        }\\r\\n\\r\\n        #endregion\\r\\n\\r\\n        #region Level 1 基础约束 - 对应遗传算法基础约束验证\\r\\n\\r\\n        /// <summary>\\r\\n        /// 添加Level 1基础约束 - 对应遗传算法的ExecuteLevel1BasicConstraintValidation\\r\\n        /// 约束内容：任务分配完整性、基本时间冲突检�?\\r\\n        /// 约束特点：必�?00%满足，违反即淘汰\\r\\n        /// </summary>\\r\\n        private async Task AddLevel1BasicConstraints(\\r\\n            Solver solver,\\r\\n            Dictionary<(long TaskId, long PersonnelId), Variable> decisionVars,\\r\\n            Dictionary<string, Variable> auxiliaryVars,\\r\\n            GlobalAllocationContext context)\\r\\n        {\\r\\n            await Task.CompletedTask;\\r\\n            var constraintCount = 0;\\r\\n            \\r\\n            _logger.LogDebug(\\\"🏗�?开始添加Level 1基础约束...\\\");\\r\\n\\r\\n            // 基础约束1：任务分配完整�?- 每个任务必须且只能分配给一个人�?\\r\\n            foreach (var task in context.Tasks)\\r\\n            {\\r\\n                var taskVariables = decisionVars.Where(v => v.Key.TaskId == task.Id).Select(v => v.Value).ToList();\\r\\n                if (taskVariables.Any())\\r\\n                {\\r\\n                    var constraint = solver.MakeConstraint(1, 1, $\\\"task_assignment_{task.Id}\\\");\\r\\n                    foreach (var variable in taskVariables)\\r\\n                    {\\r\\n                        constraint.SetCoefficient(variable, 1);\\r\\n                    }\\r\\n                    constraintCount++;\\r\\n                }\\r\\n            }\\r\\n\\r\\n            // 基础约束2：基本时间冲突约�?- 同一人员不能在同一时间段执行多个任�?\\r\\n            // 这里使用线性约束替代遗传算法中的CalculateBasicTimeConflictScore逻辑\\r\\n            foreach (var personnel in context.AvailablePersonnel)\\r\\n            {\\r\\n                // 按时间段分组检查冲�?\\r\\n                var timeGroups = context.Tasks.GroupBy(t => new { Date = t.WorkOrderDate.Date });\\r\\n                \\r\\n                foreach (var timeGroup in timeGroups)\\r\\n                {\\r\\n                    var timeSlotTasks = timeGroup.ToList();\\r\\n                    if (timeSlotTasks.Count > 1) // 同一时间段有多个任务才需要约�?\\r\\n                    {\\r\\n                        var timeSlotVariables = timeSlotTasks\\r\\n                            .Where(task => decisionVars.ContainsKey((task.Id, personnel.Id)))\\r\\n                            .Select(task => decisionVars[(task.Id, personnel.Id)])\\r\\n                            .ToList();\\r\\n\\r\\n                        if (timeSlotVariables.Count > 1)\\r\\n                        {\\r\\n                            // 约束：同一人员在同一时间段最多执�?个任�?\\r\\n                            var constraint = solver.MakeConstraint(0, 1, \\r\\n                                $\\\"time_conflict_{personnel.Id}_{timeGroup.Key.Date:yyyyMMdd}\\\");\\r\\n                            \\r\\n                            foreach (var variable in timeSlotVariables)\\r\\n                            {\\r\\n                                constraint.SetCoefficient(variable, 1);\\r\\n                            }\\r\\n                            constraintCount++;\\r\\n\\r\\n                            // 连接辅助变量（用于目标函数惩罚）\\r\\n                            var conflictVarKey = $\\\"conflict_{personnel.Id}_{timeGroup.Key.Date:yyyyMMdd}\\\";\\r\\n                            if (auxiliaryVars.ContainsKey(conflictVarKey))\\r\\n                            {\\r\\n                                // 如果分配了多个任务，冲突变量=1\\r\\n                                var conflictConstraint = solver.MakeConstraint(0, double.PositiveInfinity, \\r\\n                                    $\\\"conflict_indicator_{personnel.Id}_{timeGroup.Key.Date:yyyyMMdd}\\\");\\r\\n                                \\r\\n                                foreach (var variable in timeSlotVariables)\\r\\n                                {\\r\\n                                    conflictConstraint.SetCoefficient(variable, 1);\\r\\n                                }\\r\\n                                conflictConstraint.SetCoefficient(auxiliaryVars[conflictVarKey], -timeSlotVariables.Count + 1);\\r\\n                                constraintCount++;\\r\\n                            }\\r\\n                        }\\r\\n                    }\\r\\n                }\\r\\n            }\\r\\n\\r\\n            // 基础约束3：工作负载计算约�?- 连接决策变量与辅助变�?\\r\\n            foreach (var personnel in context.AvailablePersonnel)\\r\\n            {\\r\\n                var personnelTasks = decisionVars.Where(v => v.Key.PersonnelId == personnel.Id).ToList();\\r\\n                if (personnelTasks.Any() && auxiliaryVars.ContainsKey($\\\"workload_{personnel.Id}\\\"))\\r\\n                {\\r\\n                    var constraint = solver.MakeConstraint(0, 0, $\\\"workload_calc_{personnel.Id}\\\");\\r\\n                    \\r\\n                    foreach (var kvp in personnelTasks)\\r\\n                    {\\r\\n                        constraint.SetCoefficient(kvp.Value, 1);\\r\\n                    }\\r\\n                    constraint.SetCoefficient(auxiliaryVars[$\\\"workload_{personnel.Id}\\\"], -1);\\r\\n                    constraintCount++;\\r\\n                }\\r\\n            }\\r\\n\\r\\n            _logger.LogDebug(\\\"�?Level 1基础约束添加完成 - 约束数量：{ConstraintCount}\\\", constraintCount);\\r\\n        }\\r\\n\\r\\n        #endregion\\r\\n\\r\\n        #region Level 2 组合约束 - 对应遗传算法组合约束验证\\r\\n\\r\\n        /// <summary>\\r\\n        /// 添加Level 2组合约束 - 对应遗传算法的ExecuteLevel2CombinationConstraintValidation\\r\\n        /// 约束内容：动态班次规则、跨任务资源竞争约束\\r\\n        /// 约束特点：基于任务组合的动态验证，违反时重度惩�?\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.3}}"}}
{"timestamp":"2025-09-22T13:28:24.527Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:28:26.298Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Continuing to review constraints and objectives**"}}
{"timestamp":"2025-09-22T13:28:27.186Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":52029,"cached_input_tokens":42240,"output_tokens":1268,"reasoning_output_tokens":832,"total_tokens":53297},"last_token_usage":{"input_tokens":12892,"cached_input_tokens":11392,"output_tokens":76,"reasoning_output_tokens":0,"total_tokens":12968},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:28:27.186Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Continuing to review constraints and objectives**"}],"content":null,"encrypted_content":"gAAAAABo0U77WIDDudPB7OhyKLDAEZzLcMPq88WECsQzNl3yGtqzLaJAHoLhp-IWiSm6zVpOwPE8I6Aq0s3PlZLrKvVZBn0a1duy-XGdk3aMoqAW7FjvVBHMRBd7QoLa2tSZSkhujS84Qj3Ke4YLxbrHCCWvgGX04blOugOQ5S1epeQ3erlexBfWaBuYeV4sB60wSJTJntU-X1ocj7cKnX315XvQDDn_Qk0daNdMi5Nb4IEkdHC4SUtgEP2-rjd7ZXigl3sCORHIYUvt80fZ86LRFHg6b7VzNMhIJ4BeRZ401i4uGwxckt9Jakh2_b7d3nLduQjI45a1IA6pGH_MOxlS4hBRpJHG6lYdLH0pMSkpb6eTl-1GoVSy3zaVvDxl52-immZbNv92to_8n-tX8fU0U90UsjH2CFMo0IBJwbnCX7XivK9f_wKa3yrH_m9koGNXL_y3Cl3YqdOxZin9DvDjOVvMFU5h9o_WhbjOvcVPYak2hCDvJAhs-oKOJ66euMggiIrZuHU7gs0S-Q6Znt351angXDA_NaTti3ySYx3iPOOJDVmA9tbU5AUzIc8zVYQ3-GJgW-2vsKt7G75zTXdxRySyMmugzEsboSwtJmezGsGcJ_GEmUpFMa_Czjp0pwuizNuOKcCT09-xnLmc2HXUFjjZSLk2OHqzVpVd5tUY78D3XudMFrUrHXYCPLjn8vMjX5nNbX3CbWEBw5Bf_7m3Q2LT7uQ5VUTtwBD8OJGWfdU-X7_zo2EwL-_0ueKTQ7d2dtQDoeDkVbtMo0oBMQrrKFhsLbiyAtQucpXvLLLCuU45d7BHxo5KdtCptqGh8cyBWL-sK81VQwE4OnN64ku3buz7WxSzxEz4hpi0u-m2r4iHGCTrGGpgaZx5w2rrjQEKs0u6OrYv8_umFMRPwKYo8Kbq3WKud-cdgxzn3gwcoc7nw-2XfcxW2SdcubOo4b56fZJv8aZD4ykTlBxlRZujextfCP8Wwg=="}}
{"timestamp":"2025-09-22T13:28:27.186Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"Get-Content \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\" | Select-Object -Skip 380 -First 140\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_oS8w7MkFh4UvdUV83oolRAuv"}}
{"timestamp":"2025-09-22T13:28:27.186Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_oS8w7MkFh4UvdUV83oolRAuv","output":"{\"output\":\"        /// </summary>\\r\\n        private async Task AddLevel2CombinationConstraints(\\r\\n            Solver solver,\\r\\n            Dictionary<(long TaskId, long PersonnelId), Variable> decisionVars,\\r\\n            Dictionary<string, Variable> auxiliaryVars,\\r\\n            GlobalAllocationContext context)\\r\\n        {\\r\\n            var constraintCount = 0;\\r\\n            \\r\\n            _logger.LogDebug(\\\"🔄 开始添加Level 2组合约束...\\\");\\r\\n\\r\\n            // 组合约束1：动态班次规则约�?- 对应CalculateDynamicShiftRuleScore\\r\\n            //constraintCount += await AddDynamicShiftRuleConstraints(solver, decisionVars, auxiliaryVars, context);\\r\\n            \\r\\n            // 组合约束3：人员日工作量限制约�?\\r\\n            //constraintCount += AddDailyWorkloadConstraints(solver, decisionVars, auxiliaryVars, context);\\r\\n\\r\\n            _logger.LogDebug(\\\"�?Level 2组合约束添加完成 - 约束数量：{ConstraintCount}\\\", constraintCount);\\r\\n        }\\r\\n\\r\\n        /// <summary>\\r\\n        /// 【架构重构】添加增强版批次感知班次规则约束 - 真正解决批次验证问题\\r\\n        /// 【核心创新】：集成批次感知验证，考虑当前分配组合与历史数据的整体验证\\r\\n        /// 【深度实现】：使用PersonnelTaskMatrix进行高效的关联查询和冲突检�?\\r\\n        /// 【Ultra think级别】：从根本上解决单任�?历史验证的架构缺�?\\r\\n        /// </summary>\\r\\n        private async Task<int> AddDynamicShiftRuleConstraints(\\r\\n            Solver solver,\\r\\n            Dictionary<(long TaskId, long PersonnelId), Variable> decisionVars,\\r\\n            Dictionary<string, Variable> auxiliaryVars,\\r\\n            GlobalAllocationContext context)\\r\\n        {\\r\\n            var constraintCount = 0;\\r\\n            _logger.LogInformation(\\\"🚀 启动增强版批次感知班次规则约束构�?..\\\");\\r\\n\\r\\n            // 【架构创�?】构建人员任务关联矩阵，支持高效的批次验�?\\r\\n            var personnelTaskMatrix = BuildPersonnelTaskMatrix(decisionVars, context);\\r\\n            _logger.LogDebug(\\\"📊 人员任务矩阵构建完成 - 人员映射：{PersonnelCount}，任务映射：{TaskCount}\\\", \\r\\n                personnelTaskMatrix.PersonnelTaskMap.Count, personnelTaskMatrix.TaskPersonnelMap.Count);\\r\\n\\r\\n            // 【架构创�?】为每个人员构建批次感知的验证上下文\\r\\n            var batchValidationResults = new Dictionary<long, Dictionary<long, List<string>>>();\\r\\n            \\r\\n            foreach (var personnelEntry in personnelTaskMatrix.PersonnelTaskMap)\\r\\n            {\\r\\n                var personnelId = personnelEntry.Key;\\r\\n                var possibleTasks = personnelEntry.Value;\\r\\n                \\r\\n                if (possibleTasks.Count > 1) // 只对有多个可能任务的人员进行批次验证\\r\\n                {\\r\\n                    batchValidationResults[personnelId] = await ExecuteBatchAwareValidationAsync(\\r\\n                        personnelId, possibleTasks, context, personnelTaskMatrix);\\r\\n                }\\r\\n            }\\r\\n\\r\\n            // 【架构创�?】基于批次验证结果创建约�?\\r\\n            var shiftViolationVars = new Dictionary<string, Variable>();\\r\\n            \\r\\n            foreach (var kvp in decisionVars)\\r\\n            {\\r\\n                var (taskId, personnelId) = kvp.Key;\\r\\n                var assignmentVar = kvp.Value;\\r\\n                \\r\\n                // 创建该分配的班次规则违规指示变量\\r\\n                var violationVarKey = $\\\"batch_aware_shift_violation_{taskId}_{personnelId}\\\";\\r\\n                var violationVar = solver.MakeBoolVar(violationVarKey);\\r\\n                shiftViolationVars[violationVarKey] = violationVar;\\r\\n                \\r\\n                // 【批次感知验证】检查该分配在批次上下文中的合规�?\\r\\n                var hasViolation = false;\\r\\n                \\r\\n                if (batchValidationResults.TryGetValue(personnelId, out var personnelValidationResults))\\r\\n                {\\r\\n                    if (personnelValidationResults.TryGetValue(taskId, out var violations))\\r\\n                    {\\r\\n                        hasViolation = violations.Any();\\r\\n                        \\r\\n                        if (hasViolation)\\r\\n                        {\\r\\n                            _logger.LogDebug(\\\"📋 批次感知验证发现冲突 - 任务{TaskId}人员{PersonnelId}：{Violations}\\\", \\r\\n                                taskId, personnelId, string.Join(\\\"; \\\", violations.Take(2)));\\r\\n                        }\\r\\n                    }\\r\\n                }\\r\\n                else\\r\\n                {\\r\\n                    // 【后备验证】单任务人员使用传统验证\\r\\n                    var task = context.Tasks.FirstOrDefault(t => t.Id == taskId);\\r\\n                    if (task != null)\\r\\n                    {\\r\\n                        var otherAssignments = BuildValidationContext(personnelId, taskId, context, decisionVars);\\r\\n                        var conflicts = await _shiftRuleEngine.ValidateShiftRulesWithEnhancedBatchContextAsync(\\r\\n                            personnelId, task, otherAssignments, context);\\r\\n                        hasViolation = conflicts.Any();\\r\\n                    }\\r\\n                }\\r\\n\\r\\n                // 【约束建模】基于验证结果创建约�?\\r\\n                if (hasViolation)\\r\\n                {\\r\\n                    // 如果存在冲突，当分配该任务时违规变量必须�?\\r\\n                    var violationConstraint = solver.MakeConstraint(0, double.PositiveInfinity,\\r\\n                        $\\\"batch_force_violation_{taskId}_{personnelId}\\\");\\r\\n                    \\r\\n                    violationConstraint.SetCoefficient(assignmentVar, 1);\\r\\n                    violationConstraint.SetCoefficient(violationVar, -1);\\r\\n                    constraintCount++;\\r\\n                }\\r\\n                else\\r\\n                {\\r\\n                    // 无冲突时强制违规变量�?\\r\\n                    var noViolationConstraint = solver.MakeConstraint(0, 0,\\r\\n                        $\\\"batch_no_violation_{taskId}_{personnelId}\\\");\\r\\n                    noViolationConstraint.SetCoefficient(violationVar, 1);\\r\\n                    constraintCount++;\\r\\n                }\\r\\n            }\\r\\n\\r\\n            // 【架构创�?】添加全局批次完整性约�?\\r\\n            constraintCount += CreateGlobalTimeSlotConstraints(solver, decisionVars, context);\\r\\n            constraintCount += CreateBatchIntegrityConstraints(solver, decisionVars, auxiliaryVars, context);\\r\\n            \\r\\n            // 【全局约束】总违规数量限�?\\r\\n            var totalViolations = shiftViolationVars.Values.ToList();\\r\\n            if (totalViolations.Any())\\r\\n            {\\r\\n                var maxAllowedViolations = Math.Max(1, context.Tasks.Count / 10);\\r\\n                var totalViolationConstraint = solver.MakeConstraint(0, maxAllowedViolations, \\\"max_batch_shift_violations\\\");\\r\\n                \\r\\n                foreach (var violationVar in totalViolations)\\r\\n                {\\r\\n                    totalViolationConstraint.SetCoefficient(violationVar, 1);\\r\\n                }\\r\\n                constraintCount++;\\r\\n                \\r\\n                // 将违规变量添加到辅助变量集合�?\\r\\n                foreach (var kvp in shiftViolationVars)\\r\\n                {\\r\\n                    auxiliaryVars[kvp.Key] = kvp.Value;\\r\\n                }\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.3}}"}}
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{"timestamp":"2025-09-22T13:28:29.254Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Continuing process**"}],"content":null,"encrypted_content":"gAAAAABo0U79863kej6ON5de7LVxXs61-1pquYv-t01U2Rid54fGrfFwuLhD3LnHz0Dsd61njPe9_WFZb95o4g2bHhc79nw3KBCZVsW2KSNixow35FVP0t0YS8ndSxSzZ0YPLtUGMiYtxJSIaZml8JkqJpjy04Z0WtjiyRZuukQYZZVry-jI838uIe67np8wfJ1pOU67rCj3VkQbOT3dpIHnp2e_nVZZOW9kckZ6snsR0m1FPLdtbXlY9l_c7pBaJlieEAveWUX412FnIFlRl2XLsp5MRveL77RaaDGKuW5KbGIypdTrrDAtAf6LN1jw12dQTbcet0W2fUfP0Ke8fh-rFBQiDC_Nx9pgZXB5-bEDDqdvPXeQuJBpnMt_qIJgec88wltrGsYCVBK1CU9oknHm5hFFYDsdEy5C7G5FBGraNFOB2vTnm4xHDZeMEnXq6d2fJMUFlV31XCjEWRnmEMEcN3PtgbP3aJbCGAcQqzosA6C0I85rRoR5M-T_A5K81pdMs6iM3ZYFhrTg_7aU4hHXYZqBxHjpztmd50jFxMb3jOMFJ3OQDjOmYoJ8NRQwnVO4FcWay00yg6M3_TeAon1QqNvGZuymt6RmuIoVO-uleKWGs5Ko-XQrhJEPom7CXbtLRvmur2P88pR9NuzrlSUlWlBc4bk6__PLFQqfJI2VqkoaKOg2GLPBu_WjAtuW247Yncdhea92irYKBLJxNWONKYT7S3Wj6z7O2d1tXBeOm6AV0KbJ3tRJQKTDpO6iuQV8gbxjpG6aaNJGyGvPTC6uXXdL8VnmwueJmHfT7XvdGl39V4H30gE5SxDGcTx8JoGGLLUDVTk0bZ3vDaia1YAN0RqRIN_E_tJ0ozM5HOFAzD8nA4Zydcc="}}
{"timestamp":"2025-09-22T13:28:29.254Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"Get-Content \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\" | Select-Object -Skip 520 -First 140\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_aiaASXXcuYBMUHcdmqXgFi6K"}}
{"timestamp":"2025-09-22T13:28:29.254Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_aiaASXXcuYBMUHcdmqXgFi6K","output":"{\"output\":\"            }\\r\\n\\r\\n            _logger.LogInformation(\\\"�?增强版批次感知班次规则约束构建完�?- 约束数量：{ConstraintCount}，批次验证人员：{BatchPersonnelCount}，违规变量：{ViolationVarCount}\\\", \\r\\n                constraintCount, batchValidationResults.Count, shiftViolationVars.Count);\\r\\n            return constraintCount;\\r\\n        }\\r\\n        \\r\\n        /// <summary>\\r\\n        /// 添加日工作量约束 - 限制人员每日工作负载\\r\\n        /// </summary>\\r\\n        private int AddDailyWorkloadConstraints(\\r\\n            Solver solver,\\r\\n            Dictionary<(long TaskId, long PersonnelId), Variable> decisionVars,\\r\\n            Dictionary<string, Variable> auxiliaryVars,\\r\\n            GlobalAllocationContext context)\\r\\n        {\\r\\n            var constraintCount = 0;\\r\\n            const int maxDailyHours = 8; // 每日最大工作时长（包含加班�?\\r\\n\\r\\n            foreach (var personnel in context.AvailablePersonnel)\\r\\n            {\\r\\n                // 按日期分组该人员的任�?\\r\\n                var dailyGroups = context.Tasks\\r\\n                    .Where(t => decisionVars.ContainsKey((t.Id, personnel.Id)))\\r\\n                    .GroupBy(t => t.WorkOrderDate.Date);\\r\\n\\r\\n                foreach (var dailyGroup in dailyGroups)\\r\\n                {\\r\\n                    var dailyTasks = dailyGroup.ToList();\\r\\n                    \\r\\n                    var constraint = solver.MakeConstraint(0, maxDailyHours, \\r\\n                        $\\\"daily_workload_{personnel.Id}_{dailyGroup.Key:yyyyMMdd}\\\");\\r\\n\\r\\n                    foreach (var task in dailyTasks)\\r\\n                    {\\r\\n                        var estimatedHours = task.EstimatedHours ?? 1.0m; // 默认1小时\\r\\n                        constraint.SetCoefficient(decisionVars[(task.Id, personnel.Id)], (double)estimatedHours);\\r\\n                    }\\r\\n                    constraintCount++;\\r\\n                }\\r\\n            }\\r\\n\\r\\n            _logger.LogDebug(\\\"�?日工作量约束构建完成 - 约束数量：{WorkloadConstraintCount}\\\", constraintCount);\\r\\n            return constraintCount;\\r\\n        }\\r\\n\\r\\n        #endregion\\r\\n\\r\\n        #region Level 3 业务约束 - 对应遗传算法业务逻辑验证\\r\\n\\r\\n        /// <summary>\\r\\n        /// 添加Level 3业务约束 - 对应遗传算法的ExecuteLevel3BusinessLogicValidation\\r\\n        /// 约束内容：FL优先级规则、人员技能匹配、项目连续性约�?\\r\\n        /// 约束特点：业务规则严格执行，允许一定弹性但必须符合核心业务逻辑\\r\\n        /// </summary>\\r\\n        private async Task AddLevel3BusinessConstraints(\\r\\n            Solver solver,\\r\\n            Dictionary<(long TaskId, long PersonnelId), Variable> decisionVars,\\r\\n            Dictionary<string, Variable> auxiliaryVars,\\r\\n            GlobalAllocationContext context)\\r\\n        {\\r\\n            await Task.CompletedTask;\\r\\n            var constraintCount = 0;\\r\\n            \\r\\n            _logger.LogDebug(\\\"💼 开始添加Level 3业务约束...\\\");\\r\\n\\r\\n            // 业务约束1：FL优先级规�?- 对应CalculateFLPriorityRuleScore\\r\\n            //constraintCount += AddFLPriorityConstraints(solver, decisionVars, auxiliaryVars, context);\\r\\n\\r\\n            // 业务约束2：人员技能匹配约�?- 对应CalculateSkillMatchingConstraintScore\\r\\n            //constraintCount += AddSkillMatchingConstraints(solver, decisionVars, auxiliaryVars, context);\\r\\n\\r\\n            // 业务约束3：项目连续性约�?- 对应CalculateProjectContinuityConstraintScore\\r\\n            //constraintCount += AddProjectContinuityConstraints(solver, decisionVars, auxiliaryVars, context);\\r\\n\\r\\n            // 业务约束4：人员资质约�?- 确保只分配给具备相应资质的人�?\\r\\n            //constraintCount += await AddQualificationConstraints(solver, decisionVars, context);\\r\\n            \\r\\n            // 业务约束5：【Ultra think】人员班次不可用性硬约束 - 确保不会分配给不可用人员\\r\\n            //constraintCount += await AddPersonnelUnavailabilityConstraints(solver, decisionVars, context);\\r\\n            \\r\\n            _logger.LogDebug(\\\"�?Level 3业务约束添加完成 - 约束数量：{ConstraintCount}\\\", constraintCount);\\r\\n        }\\r\\n\\r\\n        /// <summary>\\r\\n        /// 添加FL优先级约�?- 对应遗传算法的FL优先级规则验�?\\r\\n        /// 规则10：优先分配本项目FL人员\\r\\n        /// </summary>\\r\\n        private int AddFLPriorityConstraints(\\r\\n            Solver solver,\\r\\n            Dictionary<(long TaskId, long PersonnelId), Variable> decisionVars,\\r\\n            Dictionary<string, Variable> auxiliaryVars,\\r\\n            GlobalAllocationContext context)\\r\\n        {\\r\\n            var constraintCount = 0;\\r\\n\\r\\n            foreach (var task in context.Tasks)\\r\\n            {\\r\\n                // 获取该任务关联的FL人员\\r\\n                var taskFLPersonnel = task.WorkOrderFLPersonnels?\\r\\n                    .Select(fl => fl.FLPersonnelId)\\r\\n                    .Where(flId => context.AvailablePersonnel.Any(p => p.Id == flId))\\r\\n                    .ToList() ?? new List<long>();\\r\\n\\r\\n                if (taskFLPersonnel.Any())\\r\\n                {\\r\\n                    // 创建FL优先约束：优先分配给FL人员，如果分配给非FL人员则记录违�?\\r\\n                    var flViolationVarKey = $\\\"fl_violation_{task.Id}\\\";\\r\\n                    if (auxiliaryVars.ContainsKey(flViolationVarKey))\\r\\n                    {\\r\\n                        var constraint = solver.MakeConstraint(0, double.PositiveInfinity, $\\\"fl_priority_{task.Id}\\\");\\r\\n                        \\r\\n                        // FL人员分配变量\\r\\n                        foreach (var flPersonnelId in taskFLPersonnel)\\r\\n                        {\\r\\n                            if (decisionVars.ContainsKey((task.Id, flPersonnelId)))\\r\\n                            {\\r\\n                                constraint.SetCoefficient(decisionVars[(task.Id, flPersonnelId)], 1);\\r\\n                            }\\r\\n                        }\\r\\n                        \\r\\n                        // 非FL人员分配变量\\r\\n                        var nonFLPersonnel = context.AvailablePersonnel\\r\\n                            .Where(p => !taskFLPersonnel.Contains(p.Id))\\r\\n                            .ToList();\\r\\n                            \\r\\n                        foreach (var nonFL in nonFLPersonnel)\\r\\n                        {\\r\\n                            if (decisionVars.ContainsKey((task.Id, nonFL.Id)))\\r\\n                            {\\r\\n                                constraint.SetCoefficient(decisionVars[(task.Id, nonFL.Id)], -1);\\r\\n                            }\\r\\n                        }\\r\\n                        \\r\\n                        // 违规指示变量\\r\\n                        constraint.SetCoefficient(auxiliaryVars[flViolationVarKey], 1);\\r\\n                        constraintCount++;\\r\\n                    }\\r\\n                }\\r\\n            }\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.3}}"}}
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{"timestamp":"2025-09-22T13:28:30.803Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Continuing process**"}}
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{"timestamp":"2025-09-22T13:28:31.903Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Continuing process**"}],"content":null,"encrypted_content":"gAAAAABo0U7_bdlw_G5HhUVXgsw-TrfRAbjo0A46gLIUFYoOPvj7kAKDsqKUvOyktcsmsRrIODYWiZkSUz6iddDgt8aIznXJ2UAo1uVzgKKCGCVJbAbHkGpE5WE4RBAD4Z4cPxgHb7k9tzt2M04O5L4GDs3v1PYUe2ENsMHwOJCmgHPSpQvkPd5wToqqf-YAWQqrWQL6TiJWSP_s9t0p7gdQNCLQRXDFO8C0_kMRp5lRnmvK9gRAF3ojZaTV5s-MUkqw9Lh4JUgevPVvffzaoj6oszSQa_93OpM7ZgQVq4GrU31DjvW8qlDJCa8Z6qxerKYkOn4YE2S3qATBvWl27cy3qdycX8vw5XZDrzdNh1hzOhv6ce5lkWTbMzNa57GhPXcj8kJDv1BCCR3PUs_OyiPreKAyvbRONfBK8VYkq3ydci2i5a34okj2EeGYZcd5OXt-w9aanssRoHu6VJ-RDhvWsJahvmPzKszYykNYBklIfqt8mQSSf3zRWFmdjJ8ew5r_ms-kcet648I_wZbdGiI_HZSmn6d2sHI3oC0jKYlF5ttsPsZJaAuwlgXsxV3eV7rtH9oVFXaVuAtoRIFIQ24N_KWT79davnHP-hvhYXIdTpBqKXBwmGavZJoSmWRfLNE2x6e5cWVA_eohsqoUHWhsWlpGP9YvURa-gTo6Xi67ob93yUi7zXuFBGygafvL2ozgvE2H3eC4OI1UUXLCPpnOW4uNpF-BluuQiedKf9EgPiHE5lkOQh44BTpVBR5nGzSELn_Ydkio83cKMGLN96FwDdZeV7YFOdZWKkt37tpNtvwed8VQ3fGBj8wxeDZ53vZgNXUiOgl9gbPYfZbPN6q3BubzAb677-Lxhg1Qfxwgo2qwgaiFjYM="}}
{"timestamp":"2025-09-22T13:28:31.903Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"Get-Content \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\" | Select-Object -Skip 660 -First 140\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_vq2AI8Ooyuoxudli8oEQFaxn"}}
{"timestamp":"2025-09-22T13:28:31.903Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_vq2AI8Ooyuoxudli8oEQFaxn","output":"{\"output\":\"\\r\\n            _logger.LogDebug(\\\"�?FL优先级约束构建完�?- 约束数量：{FLConstraintCount}\\\", constraintCount);\\r\\n            return constraintCount;\\r\\n        }\\r\\n\\r\\n        /// <summary>\\r\\n        /// 【重构简化】技能匹配约�?- 基于预筛选结果的轻量级实�?\\r\\n        /// 【架构优化】：移除复杂的多源资质逻辑，依赖预筛选阶段的专业验证\\r\\n        /// 【职责分离】：技能匹配交由ContextBuilderEngine处理，这里仅做约束应�?\\r\\n        /// </summary>\\r\\n        private int AddSkillMatchingConstraints(\\r\\n            Solver solver,\\r\\n            Dictionary<(long TaskId, long PersonnelId), Variable> decisionVars,\\r\\n            Dictionary<string, Variable> auxiliaryVars,\\r\\n            GlobalAllocationContext context)\\r\\n        {\\r\\n            var constraintCount = 0;\\r\\n            \\r\\n            _logger.LogDebug(\\\"🔍 开始构建技能匹配约�?- 基于预筛选结�?);\\r\\n\\r\\n            foreach (var kvp in decisionVars)\\r\\n            {\\r\\n                var (taskId, personnelId) = kvp.Key;\\r\\n                var variable = kvp.Value;\\r\\n                \\r\\n                // 【简化实现】使用预筛选结果中的技能匹配评�?\\r\\n                var prefilterKey = $\\\"{taskId}_{personnelId}\\\";\\r\\n                \\r\\n                if (context.PrefilterResults.TryGetValue(prefilterKey, out var prefilterResult))\\r\\n                {\\r\\n                    // 检查预筛选评分，低分表示技能不匹配\\r\\n                    if (prefilterResult.PrefilterScore < 30.0) // 技能匹配阈�?\\r\\n                    {\\r\\n                        // 软约束：技能不匹配允许分配但施加惩�?\\r\\n                        // 这里不设硬约束，而是通过目标函数中的评分机制处理\\r\\n                        _logger.LogTrace(\\\"⚠️ 技能匹配度较低 - 任务{TaskId}人员{PersonnelId}：评分{Score}\\\", \\r\\n                            taskId, personnelId, prefilterResult.PrefilterScore);\\r\\n                    }\\r\\n                }\\r\\n            }\\r\\n\\r\\n            _logger.LogDebug(\\\"�?技能匹配约束构建完�?- 约束数量：{SkillConstraintCount}（基于预筛选评分）\\\", constraintCount);\\r\\n            return constraintCount;\\r\\n        }\\r\\n\\r\\n        /// <summary>\\r\\n        /// 添加项目连续性约�?- 确保同项目任务由相对稳定的团队执�?\\r\\n        /// </summary>\\r\\n        private int AddProjectContinuityConstraints(\\r\\n            Solver solver,\\r\\n            Dictionary<(long TaskId, long PersonnelId), Variable> decisionVars,\\r\\n            Dictionary<string, Variable> auxiliaryVars,\\r\\n            GlobalAllocationContext context)\\r\\n        {\\r\\n            var constraintCount = 0;\\r\\n\\r\\n            // 按项目分组任�?\\r\\n            var projectGroups = context.Tasks\\r\\n                .GroupBy(t => ExtractProjectFromWorkOrderCode(t.WorkOrderCode))\\r\\n                .Where(g => !string.IsNullOrEmpty(g.Key) && g.Count() > 1)\\r\\n                .ToList();\\r\\n\\r\\n            foreach (var projectGroup in projectGroups)\\r\\n            {\\r\\n                var projectTasks = projectGroup.ToList();\\r\\n                \\r\\n                // 限制项目人员数量，促进连续�?\\r\\n                var maxProjectPersonnel = Math.Max(2, projectTasks.Count / 2);\\r\\n                \\r\\n                // 为项目创建人员参与指示变�?\\r\\n                var projectPersonnelVars = new Dictionary<long, Variable>();\\r\\n                foreach (var personnel in context.AvailablePersonnel)\\r\\n                {\\r\\n                    var participationVar = solver.MakeBoolVar($\\\"project_participation_{projectGroup.Key}_{personnel.Id}\\\");\\r\\n                    projectPersonnelVars[personnel.Id] = participationVar;\\r\\n                    \\r\\n                    // 如果人员参与项目，则至少分配一个任�?\\r\\n                    var constraint = solver.MakeConstraint(0, double.PositiveInfinity, \\r\\n                        $\\\"project_min_tasks_{projectGroup.Key}_{personnel.Id}\\\");\\r\\n                    \\r\\n                    constraint.SetCoefficient(participationVar, -1);\\r\\n                    \\r\\n                    foreach (var task in projectTasks)\\r\\n                    {\\r\\n                        if (decisionVars.ContainsKey((task.Id, personnel.Id)))\\r\\n                        {\\r\\n                            constraint.SetCoefficient(decisionVars[(task.Id, personnel.Id)], 1);\\r\\n                        }\\r\\n                    }\\r\\n                    constraintCount++;\\r\\n                }\\r\\n                \\r\\n                // 限制项目参与人员总数\\r\\n                var personnelLimitConstraint = solver.MakeConstraint(0, maxProjectPersonnel, \\r\\n                    $\\\"project_personnel_limit_{projectGroup.Key}\\\");\\r\\n                \\r\\n                foreach (var kvp in projectPersonnelVars)\\r\\n                {\\r\\n                    personnelLimitConstraint.SetCoefficient(kvp.Value, 1);\\r\\n                }\\r\\n                constraintCount++;\\r\\n            }\\r\\n\\r\\n            _logger.LogDebug(\\\"�?项目连续性约束构建完�?- 约束数量：{ContinuityConstraintCount}\\\", constraintCount);\\r\\n            return constraintCount;\\r\\n        }\\r\\n\\r\\n        /// <summary>\\r\\n        /// 【重构优化】添加人员资质约�?- 基于ContextBuilderEngine的成熟实�?\\r\\n        /// 【架构改进】：复用预构建的预筛选结果，避免重复的资质验证逻辑\\r\\n        /// 【性能优化】：利用PrefilterResults缓存，实现O(1)查询复杂�?\\r\\n        /// 【一致性保证】：与ContextBuilderEngine使用完全相同的资质验证标�?\\r\\n        /// </summary>\\r\\n        private async Task<int> AddQualificationConstraints(\\r\\n            Solver solver,\\r\\n            Dictionary<(long TaskId, long PersonnelId), Variable> decisionVars,\\r\\n            GlobalAllocationContext context)\\r\\n        {\\r\\n            var constraintCount = 0;\\r\\n            \\r\\n            _logger.LogDebug(\\\"🔍 开始构建资质约�?- 基于预筛选结果的高效实现\\\");\\r\\n\\r\\n            foreach (var kvp in decisionVars)\\r\\n            {\\r\\n                var (taskId, personnelId) = kvp.Key;\\r\\n                var variable = kvp.Value;\\r\\n                \\r\\n                // 【核心改进】直接使用预筛选结果中的资质验证结�?\\r\\n                var prefilterKey = $\\\"{taskId}_{personnelId}\\\";\\r\\n                \\r\\n                if (context.PrefilterResults.TryGetValue(prefilterKey, out var prefilterResult))\\r\\n                {\\r\\n                    // 检查预筛选结果中是否包含资质相关的违�?\\r\\n                    var hasQualificationViolation = prefilterResult.ConstraintViolations\\r\\n                        .Any(violation => violation.Contains(\\\"资质\\\") || violation.Contains(\\\"qualification\\\"));\\r\\n                    \\r\\n                    if (hasQualificationViolation)\\r\\n                    {\\r\\n                        // 硬约束：预筛选发现资质违规，禁止此分�?\\r\\n                        var constraint = solver.MakeConstraint(0, 0, $\\\"prefilter_qualification_{taskId}_{personnelId}\\\");\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.3}}"}}
{"timestamp":"2025-09-22T13:28:31.903Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:28:33.343Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Continuing exploration**"}}
{"timestamp":"2025-09-22T13:28:34.213Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":101373,"cached_input_tokens":86016,"output_tokens":1496,"reasoning_output_tokens":832,"total_tokens":102869},"last_token_usage":{"input_tokens":18215,"cached_input_tokens":16384,"output_tokens":76,"reasoning_output_tokens":0,"total_tokens":18291},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:28:34.214Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Continuing exploration**"}],"content":null,"encrypted_content":"gAAAAABo0U8C0jUhyIbCLO923g18hhswnBUe2Fev1_tclrXHgqE5du19f_28EPdhZgifz_uRBBAkRv7jUae-OGCzVIpMxm2aYH2wQ-uo9asXbWuUs5nbgcNI0Ey6xET4orrymp9hD-K7Ubjvm0upqh-k5gchRO_rkmUPDlSwXt-ZTGa5TGvj3ioOwcfSkc8hWH2ZxV2rjZrZx3Cew8GtGW3d3M_f-R3OR4VCQUBfs2AMV4Zn1_0RS4CEZoFzWvr8p0dHd6aJQV_p5ryOo32iTJvNm8sbwZRtSwIsAnvz3OqvYA5fMb3lyB3NNp8hHrOI0bpCHrOm_hhHxioA5_P5rlVVfFmTwBar59QGNE0Qxj1HxO8-6reH0eFpANxhiOxRsGje7aTttAwkPNs6E8erkuam7nC9kLB5R5UiDDEzVszPGMtHEvhyrvsiLpxVOVfHSYvHtrjyULURpol1UnCMrEVhRV-LO6EgwxmkHdN0HJmp4_h28t7rayEirVvcbba5Hhg1nCg0zi_06TWFtTlHtFkf_OgLbR9OVmh4o9V6VK3Z0YqLnTdNXajkV1LN7-ZL3v1dsZ-RloY1YJaK2ILybM7KipbIHM7XJXfjh1CkBwJwmmW7SmLIHLBxNt1NYX_xaVh-3jKWC-C1mrsaNXkxX3o0kv8IspgpvqIqSkLF0hha6klgn6YlIFSwBJdWbpQp8RLF5PNPM86rOcsUC4TEHbMqTdnkqX696fTqD-PzOZ8sRkISO_GmaA3ZF7ekjettsLtktKFDHJ5eCHApnSF0e32SDIzRchIhEmpB0pKuHXfV4AvUb8119-OZ02TUlfVrRWZ_8erNvxkp30BaN1a-kISDv4ZSeTkLKG0tGpDdlM3C9GHsYpSUqGg="}}
{"timestamp":"2025-09-22T13:28:34.214Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"Get-Content \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\" | Select-Object -Skip 800 -First 140\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_RE6ffg0EMR5LsCVEnnPtThAL"}}
{"timestamp":"2025-09-22T13:28:34.214Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_RE6ffg0EMR5LsCVEnnPtThAL","output":"{\"output\":\"                        constraint.SetCoefficient(variable, 1);\\r\\n                        constraintCount++;\\r\\n                        \\r\\n                        _logger.LogTrace(\\\"🚫 资质约束应用 - 任务{TaskId}人员{PersonnelId}：{Violations}\\\", \\r\\n                            taskId, personnelId, string.Join(\\\"; \\\", prefilterResult.ConstraintViolations.Take(2)));\\r\\n                    }\\r\\n                }\\r\\n                else\\r\\n                {\\r\\n                    // 【安全保障】无预筛选数据时的后备验�?\\r\\n                    var isQualified = await CheckQualificationCompatibilityAsync(taskId, personnelId, context);\\r\\n                    if (!isQualified)\\r\\n                    {\\r\\n                        var constraint = solver.MakeConstraint(0, 0, $\\\"fallback_qualification_{taskId}_{personnelId}\\\");\\r\\n                        constraint.SetCoefficient(variable, 1);\\r\\n                        constraintCount++;\\r\\n                        \\r\\n                        _logger.LogTrace(\\\"🚫 后备资质约束应用 - 任务{TaskId}人员{PersonnelId}\\\", taskId, personnelId);\\r\\n                    }\\r\\n                }\\r\\n            }\\r\\n\\r\\n            _logger.LogInformation(\\\"�?资质约束构建完成 - 约束数量：{QualificationConstraintCount}（基于预筛选结果）\\\", constraintCount);\\r\\n            return constraintCount;\\r\\n        }\\r\\n\\r\\n        #endregion\\r\\n\\r\\n        #region 公平性约�?- 对应遗传算法负载均衡机制\\r\\n\\r\\n        /// <summary>\\r\\n        /// 添加公平性约�?- 对应遗传算法的CalculateFairnessScore和负载均衡机�?\\r\\n        /// 包含：负载均衡约束、人员利用率约束、过度集中惩罚约�?\\r\\n        /// </summary>\\r\\n        private void AddFairnessConstraints(\\r\\n            Solver solver,\\r\\n            Dictionary<(long TaskId, long PersonnelId), Variable> decisionVars,\\r\\n            Dictionary<string, Variable> auxiliaryVars,\\r\\n            GlobalAllocationContext context)\\r\\n        {\\r\\n            var constraintCount = 0;\\r\\n            \\r\\n            _logger.LogInformation(\\\"⚖️ 开始添加公平性约�?..\\\");\\r\\n\\r\\n            var totalTasks = context.Tasks.Count;\\r\\n            var totalPersonnel = context.AvailablePersonnel.Count;\\r\\n            var avgWorkload = (double)totalTasks / totalPersonnel;\\r\\n\\r\\n            // 公平性约�?：负载均衡偏差计�?\\r\\n            foreach (var personnel in context.AvailablePersonnel)\\r\\n            {\\r\\n                var workloadVarKey = $\\\"workload_{personnel.Id}\\\";\\r\\n                var posDevVarKey = $\\\"pos_dev_{personnel.Id}\\\";\\r\\n                var negDevVarKey = $\\\"neg_dev_{personnel.Id}\\\";\\r\\n\\r\\n                if (auxiliaryVars.ContainsKey(workloadVarKey) && \\r\\n                    auxiliaryVars.ContainsKey(posDevVarKey) && \\r\\n                    auxiliaryVars.ContainsKey(negDevVarKey))\\r\\n                {\\r\\n                    // 约束：workload = avgWorkload + pos_deviation - neg_deviation\\r\\n                    var balanceConstraint = solver.MakeConstraint(avgWorkload, avgWorkload, \\r\\n                        $\\\"load_balance_{personnel.Id}\\\");\\r\\n                    \\r\\n                    balanceConstraint.SetCoefficient(auxiliaryVars[workloadVarKey], 1);\\r\\n                    balanceConstraint.SetCoefficient(auxiliaryVars[posDevVarKey], -1);\\r\\n                    balanceConstraint.SetCoefficient(auxiliaryVars[negDevVarKey], 1);\\r\\n                    constraintCount++;\\r\\n                }\\r\\n            }\\r\\n\\r\\n            // 公平性约�?：最大负载限�?- 防止极端不均�?\\r\\n            var maxReasonableWorkload = Math.Ceiling(avgWorkload * 1.5);\\r\\n            foreach (var personnel in context.AvailablePersonnel)\\r\\n            {\\r\\n                var workloadVarKey = $\\\"workload_{personnel.Id}\\\";\\r\\n                if (auxiliaryVars.ContainsKey(workloadVarKey))\\r\\n                {\\r\\n                    var constraint = solver.MakeConstraint(0, maxReasonableWorkload, \\r\\n                        $\\\"max_workload_{personnel.Id}\\\");\\r\\n                    constraint.SetCoefficient(auxiliaryVars[workloadVarKey], 1);\\r\\n                    constraintCount++;\\r\\n                }\\r\\n            }\\r\\n\\r\\n            // 公平性约�?：最小人员利用率约束 - 确保不会过度集中\\r\\n            var minPersonnelUtilization = totalTasks > 10 ? Math.Max(3, totalPersonnel * 0.4) : 2;\\r\\n            \\r\\n            // 创建人员参与指示变量\\r\\n            var participationVars = new List<Variable>();\\r\\n            foreach (var personnel in context.AvailablePersonnel)\\r\\n            {\\r\\n                var participationVar = solver.MakeBoolVar($\\\"participation_{personnel.Id}\\\");\\r\\n                participationVars.Add(participationVar);\\r\\n                \\r\\n                // 如果人员参与，则至少分配1个任�?\\r\\n                var constraint = solver.MakeConstraint(0, double.PositiveInfinity, \\r\\n                    $\\\"participation_min_{personnel.Id}\\\");\\r\\n                \\r\\n                constraint.SetCoefficient(participationVar, -1);\\r\\n                \\r\\n                var personnelTasks = decisionVars.Where(v => v.Key.PersonnelId == personnel.Id);\\r\\n                foreach (var kvp in personnelTasks)\\r\\n                {\\r\\n                    constraint.SetCoefficient(kvp.Value, 1);\\r\\n                }\\r\\n                constraintCount++;\\r\\n            }\\r\\n            \\r\\n            // 最小参与人数约�?\\r\\n            var minParticipationConstraint = solver.MakeConstraint(minPersonnelUtilization, double.PositiveInfinity, \\r\\n                \\\"min_personnel_utilization\\\");\\r\\n            \\r\\n            foreach (var participationVar in participationVars)\\r\\n            {\\r\\n                minParticipationConstraint.SetCoefficient(participationVar, 1);\\r\\n            }\\r\\n            constraintCount++;\\r\\n\\r\\n            _logger.LogDebug(\\\"�?公平性约束添加完�?- 约束数量：{ConstraintCount}，平均负载：{AvgWorkload:F2}，最大负载：{MaxWorkload:F2}，最小参与人数：{MinParticipation}\\\", \\r\\n                constraintCount, avgWorkload, maxReasonableWorkload, minPersonnelUtilization);\\r\\n        }\\r\\n\\r\\n        #endregion\\r\\n\\r\\n        #region 目标函数 - 对应遗传算法适应度函�?\\r\\n\\r\\n        /// <summary>\\r\\n        /// 设置增强版目标函�?- 对应遗传算法的多维度适应度评�?\\r\\n        /// 目标组成：基础评分 + 约束惩罚 + 公平性奖�?+ 业务优先级奖�?\\r\\n        /// 权重设计：约束满�?最�? > 公平�?�? > 业务优化(�? > 其他因素(�?\\r\\n        /// </summary>\\r\\n        private void SetEnhancedObjectiveFunction(\\r\\n            Solver solver,\\r\\n            Dictionary<(long TaskId, long PersonnelId), Variable> decisionVars,\\r\\n            Dictionary<string, Variable> auxiliaryVars,\\r\\n            GlobalAllocationContext context)\\r\\n        {\\r\\n            var objective = solver.Objective();\\r\\n            objective.SetMaximization();\\r\\n            \\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.3}}"}}
{"timestamp":"2025-09-22T13:28:34.214Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:28:41.099Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Proceeding to objective**"}}
{"timestamp":"2025-09-22T13:28:42.166Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":121360,"cached_input_tokens":104192,"output_tokens":1572,"reasoning_output_tokens":832,"total_tokens":122932},"last_token_usage":{"input_tokens":19987,"cached_input_tokens":18176,"output_tokens":76,"reasoning_output_tokens":0,"total_tokens":20063},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:28:42.166Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Proceeding to objective**"}],"content":null,"encrypted_content":"gAAAAABo0U8KltfDJf_4ng_bjPdagyoCHznyzNPVmoxZGph7iV20IBHKP8FeBQzfPde1Hq39Ue3I8vt3ITu3TUtSxVqxrZoivX8WGTfy6HAYXy6YvYiF33wjjw48WUYqKhb6UBRsrB6AAt0NKFPn3kFVWcgk4Ic0fkPVBP4q82jS2z7VZxCifkJXJajiaQZ8_HSEjzhPoPsfg8TEFNYznY0GB0FZiGR9bgIZrVT_2Ir23b1ZQ1Q5Infh_zQbfyTo0woAPWNXYoZvsd9yB3CI7O2ZeOSfQ08xv6IF-IJ6DiZivqt5RWrtIrubmxDHsy71-x2SFZkIP0xKWrUzVvPxoaLVpm53hsFw6_QiWHtdTmFfKL9u4z3eNJ_gRyF6KZE0xMxpFfNiMaw2yNY-mkdkeAwzGLOx75_UssHMfkDVWgngR3SDSR1Kj5HFc8vnShJzNIKw7gnUkp16QdTcc7LPMdVXf31c-Hp1fdVBwMc6-btmZOrXG3AR2RS8fg9iaO33jfQ_wSYkEKXb9znvLj9VRByFbPldd2PTKjWOxHP7zVXl8Zg1mKd67Z4qBrMid-ki6uNAa6vj3h61961Q5JWjx5rCosoAG2-6431d03z6q3MFcPvkIXlNzQgB4WlG3XtRGawYnHc7X82Fg3aqWFJCeHvr4ky9jNTgkgODcEaPDNUe53K_QIqCbmpTvdUuk61fOflQ6XQI9N05mHH-VFB5UYJMNIghQwUEn8NwmfeLESlB63Re7vNgiehRSwCsvjW9wgkPjevB_GIQeJB1_h5IkcZQ9vg8m9_7-v8mMs7FWdO3Swjwqspqk05n28diWLot9xYv-kZPfalxfyoNUa5vkkwMkIosrCuJLiuBwj_CJqA2rjDycQB0NcQWwUSmq7R31_85fGAV1Unx"}}
{"timestamp":"2025-09-22T13:28:42.166Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"Get-Content \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\" | Select-Object -Skip 940 -First 160\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_mhWSwtXpUK4ZbVmPfa5pKL3p"}}
{"timestamp":"2025-09-22T13:28:42.166Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_mhWSwtXpUK4ZbVmPfa5pKL3p","output":"{\"output\":\"            _logger.LogInformation(\\\"🎯 构建增强版多维度目标函数...\\\");\\r\\n\\r\\n            // 目标组件1：基础分配评分 - 基于预筛选结果的质量评分\\r\\n            AddBaseAssignmentScore(objective, decisionVars, context);\\r\\n\\r\\n            // 目标组件2：约束违规惩�?- 对应遗传算法的约束评�?\\r\\n            AddConstraintViolationPenalties(objective, auxiliaryVars, context);\\r\\n\\r\\n            // 目标组件3：公平性奖�?- 对应遗传算法的公平性评�?\\r\\n            AddFairnessRewards(objective, auxiliaryVars, context);\\r\\n\\r\\n            // 目标组件4：业务优先级奖励 - 对应遗传算法的业务逻辑优化\\r\\n            //AddBusinessPriorityRewards(objective, decisionVars, auxiliaryVars, context);\\r\\n\\r\\n            _logger.LogInformation(\\\"�?增强版目标函数构建完成，包含4大评分维�?);\\r\\n        }\\r\\n\\r\\n        /// <summary>\\r\\n        /// 添加基础分配评分 - 基于预筛选结果和任务-人员匹配质量\\r\\n        /// </summary>\\r\\n        private void AddBaseAssignmentScore(\\r\\n            Objective objective,\\r\\n            Dictionary<(long TaskId, long PersonnelId), Variable> decisionVars,\\r\\n            GlobalAllocationContext context)\\r\\n        {\\r\\n            foreach (var kvp in decisionVars)\\r\\n            {\\r\\n                var (taskId, personnelId) = kvp.Key;\\r\\n                var variable = kvp.Value;\\r\\n                \\r\\n                // 基础评分：基于预筛选结�?\\r\\n                var prefilterKey = $\\\"{taskId}_{personnelId}\\\";\\r\\n                var baseScore = 100.0; // 默认基础�?\\r\\n                \\r\\n                if (context.PrefilterResults.TryGetValue(prefilterKey, out var prefilterResult))\\r\\n                {\\r\\n                    baseScore = Math.Max(baseScore, prefilterResult.PrefilterScore * 2); // 放大预筛选评分的影响\\r\\n                }\\r\\n                \\r\\n                // 技能匹配奖�?\\r\\n                var task = context.Tasks.FirstOrDefault(t => t.Id == taskId);\\r\\n                if (task != null)\\r\\n                {\\r\\n                    var skillBonus = CalculateSkillMatchingBonus(task, personnelId, context);\\r\\n                    baseScore += skillBonus;\\r\\n                }\\r\\n                \\r\\n                objective.SetCoefficient(variable, baseScore);\\r\\n            }\\r\\n        }\\r\\n\\r\\n        /// <summary>\\r\\n        /// 添加约束违规惩罚 - 对应遗传算法的三级约束惩罚机�?\\r\\n        /// </summary>\\r\\n        private void AddConstraintViolationPenalties(\\r\\n            Objective objective,\\r\\n            Dictionary<string, Variable> auxiliaryVars,\\r\\n            GlobalAllocationContext context)\\r\\n        {\\r\\n            // Level 1惩罚：时间冲突严厉惩�?\\r\\n            foreach (var kvp in auxiliaryVars.Where(v => v.Key.StartsWith(\\\"conflict_\\\")))\\r\\n            {\\r\\n                objective.SetCoefficient(kvp.Value, -LEVEL1_CONSTRAINT_PENALTY);\\r\\n            }\\r\\n\\r\\n            // Level 2惩罚：班次规则违规重度惩�?\\r\\n            // foreach (var kvp in auxiliaryVars.Where(v => v.Key.StartsWith(\\\"shift_violation_\\\")))\\r\\n            // {\\r\\n            //     objective.SetCoefficient(kvp.Value, -LEVEL2_CONSTRAINT_PENALTY);\\r\\n            // }\\r\\n\\r\\n            // Level 3惩罚：业务逻辑违规中度惩罚\\r\\n            // foreach (var kvp in auxiliaryVars.Where(v => v.Key.StartsWith(\\\"fl_violation_\\\")))\\r\\n            // {\\r\\n            //     objective.SetCoefficient(kvp.Value, -LEVEL3_CONSTRAINT_PENALTY);\\r\\n            // }\\r\\n        }\\r\\n\\r\\n        /// <summary>\\r\\n        /// 添加公平性奖�?- 对应遗传算法的负载均衡评�?\\r\\n        /// </summary>\\r\\n        private void AddFairnessRewards(\\r\\n            Objective objective,\\r\\n            Dictionary<string, Variable> auxiliaryVars,\\r\\n            GlobalAllocationContext context)\\r\\n        {\\r\\n            // 负载均衡奖励：减少偏差获得奖�?\\r\\n            // foreach (var kvp in auxiliaryVars.Where(v => v.Key.StartsWith(\\\"pos_dev_\\\") || v.Key.StartsWith(\\\"neg_dev_\\\")))\\r\\n            // {\\r\\n            //     // 偏差越小，奖励越多（通过负的偏差系数实现�?\\r\\n            //     objective.SetCoefficient(kvp.Value, -FAIRNESS_REWARD_FACTOR);\\r\\n            // }\\r\\n        }\\r\\n\\r\\n        /// <summary>\\r\\n        /// 添加业务优先级奖�?- 对应遗传算法的业务规则优�?\\r\\n        /// </summary>\\r\\n        private void AddBusinessPriorityRewards(\\r\\n            Objective objective,\\r\\n            Dictionary<(long TaskId, long PersonnelId), Variable> decisionVars,\\r\\n            Dictionary<string, Variable> auxiliaryVars,\\r\\n            GlobalAllocationContext context)\\r\\n        {\\r\\n            // FL优先级奖�?\\r\\n            foreach (var task in context.Tasks)\\r\\n            {\\r\\n                var taskFLPersonnel = task.WorkOrderFLPersonnels?\\r\\n                    .Select(fl => fl.FLPersonnelId)\\r\\n                    .Where(flId => context.AvailablePersonnel.Any(p => p.Id == flId))\\r\\n                    .ToList() ?? new List<long>();\\r\\n\\r\\n                if (taskFLPersonnel.Any())\\r\\n                {\\r\\n                    foreach (var flPersonnelId in taskFLPersonnel)\\r\\n                    {\\r\\n                        if (decisionVars.ContainsKey((task.Id, flPersonnelId)))\\r\\n                        {\\r\\n                            // FL人员执行本项目任务获得奖�?\\r\\n                            objective.SetCoefficient(decisionVars[(task.Id, flPersonnelId)], 500.0);\\r\\n                        }\\r\\n                    }\\r\\n                }\\r\\n            }\\r\\n\\r\\n            // 任务优先级和紧急度奖励\\r\\n            foreach (var task in context.Tasks)\\r\\n            {\\r\\n                var priorityBonus = task.Priority * 50.0;\\r\\n                var urgencyBonus = task.Urgency * 30.0;\\r\\n                var totalBonus = priorityBonus + urgencyBonus;\\r\\n\\r\\n                var taskVariables = decisionVars.Where(v => v.Key.TaskId == task.Id);\\r\\n                foreach (var kvp in taskVariables)\\r\\n                {\\r\\n                    objective.SetCoefficient(kvp.Value, totalBonus);\\r\\n                }\\r\\n            }\\r\\n        }\\r\\n\\r\\n        #endregion\\r\\n\\r\\n        #region 结果处理和验�?\\r\\n\\r\\n        /// <summary>\\r\\n        /// 处理增强版求解器结果 - 包含完整的解析和验证逻辑\\r\\n        /// </summary>\\r\\n        private async Task<GlobalOptimizedSolution> ProcessEnhancedSolverResult(\\r\\n            Solver solver,\\r\\n            Dictionary<(long TaskId, long PersonnelId), Variable> decisionVars,\\r\\n            Dictionary<string, Variable> auxiliaryVars,\\r\\n            GlobalAllocationContext context,\\r\\n            Solver.ResultStatus resultStatus,\\r\\n            long elapsedMs)\\r\\n        {\\r\\n            var solution = new GlobalOptimizedSolution\\r\\n            {\\r\\n                ActualGenerations = 1 // 线性规划一次求�?\\r\\n            };\\r\\n\\r\\n            _logger.LogInformation(\\\"📊 开始解析增强版线性规划结�?- 状态：{Status}，耗时：{ElapsedMs}ms\\\", \\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.3}}"}}
{"timestamp":"2025-09-22T13:28:42.166Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:28:43.663Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Continuing result processing**"}}
{"timestamp":"2025-09-22T13:28:44.776Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":143197,"cached_input_tokens":124160,"output_tokens":1649,"reasoning_output_tokens":832,"total_tokens":144846},"last_token_usage":{"input_tokens":21837,"cached_input_tokens":19968,"output_tokens":77,"reasoning_output_tokens":0,"total_tokens":21914},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:28:44.776Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Continuing result processing**"}],"content":null,"encrypted_content":"gAAAAABo0U8MULTkzNhCJXKd14V6t4Q4j2SpUpreufAs76tRzqejHX_tPs-7dUWshkRtltQkE38PaaPus7bAXAm7CIvneLYrJTcijdkhzG_GRlLWpRtaqUXdC-MX8MZmZ_SccLYHS7EWc8tosJL8Ltx_jY8vUN7BfA9eE8JJPu7VbZ1AXDQZjLhazPaadMW0omsLHmEM33OhvluXNuTyBSepLR-alDL8hlL0Iv5MlZ1LBlKMsLzWOZNunUGaiTLT7T9FSWC2NQrTxu0B3ptEvnFwaXW4OPIh1uW2yOAcaWE2EvarerSBSMgsvscrevf_CfiHq3vBE72dxpPkusjxzjGHdqCi0VWIa5NSBa7iF2qKe9tvyxHqE6jUN20hr-WCyP64YGaSYmFSP44AVBj4ns3bx4a7NFLG1YpMdOGbIBuUJykhFtTiY950sNVMjlJ_dgcPugbXfJdxA5Acy77GxmCyv82QH9vZuhsHLcKHjfDjIEBMGIZ2hacJzzc-bOvBJWWYns7aGSXVJBPGW0V52OEif2OpVYZqvfcB7MJZrmP-QIfpX58NsgsOyw-CQkW-8MPtQv6xRBhvowKXbuox2hq5kJg6YkdAJNkK-9wEZp_xPHUakmDshNsjm5NClf9mZd7g160kZv2kFjM9p4Q2HXbk7TghdVbnxc4U--PVarIvW11I6NYErdXxzB32QmlzXDiBrHV0IzjIf5UbViCCK9oKSCr4Pc2orVXBI1YEOSHwMeCAmmK7U588PPDWJHhUqs1IN9uGETPGuP8nQb0HzU6AwJjR7-lkOQPzKZj3150pr6oySsSMVMBleVqjYwEYQBzCd83AOdfMf1paMI0XhlHNn8ezpgTe9Mo8nCN22ZmMnWWj56Z4Alq6FQVuilz4SJeLfU4yVRze0WzddxSu6izZKz42NlJFtA=="}}
{"timestamp":"2025-09-22T13:28:44.776Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"Get-Content \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\" | Select-Object -Skip 1100 -First 160\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_CGSNThHqH6s7VpiAU7wCJmSY"}}
{"timestamp":"2025-09-22T13:28:44.776Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_CGSNThHqH6s7VpiAU7wCJmSY","output":"{\"output\":\"                resultStatus, elapsedMs);\\r\\n\\r\\n            if (resultStatus == Solver.ResultStatus.OPTIMAL || resultStatus == Solver.ResultStatus.FEASIBLE)\\r\\n            {\\r\\n                var assignments = new Dictionary<long, long>();\\r\\n                var workloadDistribution = new Dictionary<long, decimal>();\\r\\n                var totalScore = 0.0;\\r\\n                var constraintViolations = new List<string>();\\r\\n\\r\\n                // 解析任务分配结果\\r\\n                foreach (var kvp in decisionVars)\\r\\n                {\\r\\n                    if (kvp.Value.SolutionValue() > 0.5) // 布尔变量阈�?\\r\\n                    {\\r\\n                        var (taskId, personnelId) = kvp.Key;\\r\\n                        assignments[taskId] = personnelId;\\r\\n                        \\r\\n                        workloadDistribution[personnelId] = workloadDistribution.GetValueOrDefault(personnelId, 0) + 1;\\r\\n                        \\r\\n                        // 计算分配评分\\r\\n                        var assignmentScore = CalculateAssignmentScore(taskId, personnelId, context);\\r\\n                        totalScore += assignmentScore;\\r\\n                    }\\r\\n                }\\r\\n\\r\\n                // 验证解的质量\\r\\n                var qualityMetrics = await ValidateSolutionQuality(assignments, auxiliaryVars, context);\\r\\n                \\r\\n                solution.BestSolution = assignments;\\r\\n                solution.BestFitness = solver.Objective().Value();\\r\\n                solution.PersonnelWorkloadDistribution = workloadDistribution;\\r\\n                solution.ConstraintSatisfactionRate = qualityMetrics.ConstraintSatisfactionRate;\\r\\n                // solution.QualityMetrics = qualityMetrics; // 暂时注释，等待扩展GlobalOptimizedSolution\\r\\n\\r\\n                _logger.LogInformation(\\\"�?增强版线性规划求解成�?- 目标值：{ObjectiveValue:F2}，分配任务：{TaskCount}，使用人员：{PersonnelCount}，约束满足率：{SatisfactionRate:P2}\\\",\\r\\n                    solution.BestFitness, assignments.Count, workloadDistribution.Count, qualityMetrics.ConstraintSatisfactionRate);\\r\\n\\r\\n                // 详细的工作负载分�?\\r\\n                LogWorkloadAnalysis(workloadDistribution, context.Tasks.Count, context.AvailablePersonnel.Count);\\r\\n            }\\r\\n            else\\r\\n            {\\r\\n                _logger.LogWarning(\\\"⚠️ 增强版线性规划无�?- 状态：{Status}，可能原因：约束过于严格\\\", resultStatus);\\r\\n                solution.BestSolution = new Dictionary<long, long>();\\r\\n                solution.BestFitness = 0.0;\\r\\n                solution.ConstraintSatisfactionRate = 0.0;\\r\\n                // solution.ErrorMessage = $\\\"线性规划模型无解，状态：{resultStatus}\\\"; // 暂时注释，等待扩展GlobalOptimizedSolution\\r\\n            }\\r\\n\\r\\n            return solution;\\r\\n        }\\r\\n\\r\\n        /// <summary>\\r\\n        /// 验证解的质量 - 对应遗传算法的约束满足率计算\\r\\n        /// </summary>\\r\\n        private async Task<SolutionQualityMetrics> ValidateSolutionQuality(\\r\\n            Dictionary<long, long> assignments, \\r\\n            Dictionary<string, Variable> auxiliaryVars,\\r\\n            GlobalAllocationContext context)\\r\\n        {\\r\\n            await Task.CompletedTask;\\r\\n            \\r\\n            var metrics = new SolutionQualityMetrics();\\r\\n            var violationCount = 0;\\r\\n            var totalChecks = 0;\\r\\n\\r\\n            // 检�?：任务分配完整�?\\r\\n            var completenessRate = assignments.Count > 0 ? (double)assignments.Count / context.Tasks.Count : 0.0;\\r\\n            metrics.TaskCompletenessRate = completenessRate;\\r\\n            if (completenessRate < 1.0) violationCount++;\\r\\n            totalChecks++;\\r\\n\\r\\n            // 检�?：时间冲突验�?\\r\\n            var timeConflictCount = 0;\\r\\n            var personnelTimeSlots = assignments.GroupBy(a => a.Value)\\r\\n                .ToDictionary(g => g.Key, g => g.Select(kvp => \\r\\n                {\\r\\n                    var task = context.Tasks.First(t => t.Id == kvp.Key);\\r\\n                    return new { Task = task, Date = task.WorkOrderDate.Date, ShiftId = task.ShiftId };\\r\\n                }).ToList());\\r\\n\\r\\n            foreach (var kvp in personnelTimeSlots)\\r\\n            {\\r\\n                var timeGroups = kvp.Value.GroupBy(t => new { t.Date, t.ShiftId });\\r\\n                foreach (var timeGroup in timeGroups)\\r\\n                {\\r\\n                    if (timeGroup.Count() > 1)\\r\\n                    {\\r\\n                        timeConflictCount += timeGroup.Count() - 1;\\r\\n                    }\\r\\n                }\\r\\n                totalChecks++;\\r\\n            }\\r\\n\\r\\n            metrics.TimeConflictRate = totalChecks > 0 ? (double)timeConflictCount / totalChecks : 0.0;\\r\\n            if (timeConflictCount > 0) violationCount++;\\r\\n\\r\\n            // 检�?：负载均衡评�?\\r\\n            if (assignments.Any())\\r\\n            {\\r\\n                var workloadValues = personnelTimeSlots.Values.Select(v => (decimal)v.Count).ToList();\\r\\n                var giniCoefficient = CalculateGiniCoefficient(workloadValues);\\r\\n                metrics.LoadBalanceScore = Math.Max(0.0, 1.0 - giniCoefficient);\\r\\n                \\r\\n                var utilizationRate = (double)personnelTimeSlots.Count / context.AvailablePersonnel.Count;\\r\\n                metrics.PersonnelUtilizationRate = utilizationRate;\\r\\n            }\\r\\n\\r\\n            // 综合约束满足�?\\r\\n            metrics.ConstraintSatisfactionRate = totalChecks > 0 ? \\r\\n                Math.Max(0.0, 1.0 - (double)violationCount / totalChecks) : 1.0;\\r\\n\\r\\n            return metrics;\\r\\n        }\\r\\n\\r\\n        /// <summary>\\r\\n        /// 记录详细的工作负载分析日�?\\r\\n        /// </summary>\\r\\n        private void LogWorkloadAnalysis(Dictionary<long, decimal> workloadDistribution, int totalTasks, int totalPersonnel)\\r\\n        {\\r\\n            if (!workloadDistribution.Any()) return;\\r\\n\\r\\n            var workloads = workloadDistribution.Values.ToList();\\r\\n            var avgWorkload = workloads.Average(w => (double)w);\\r\\n            var maxWorkload = workloads.Max();\\r\\n            var minWorkload = workloads.Min();\\r\\n            var utilizationRate = (double)workloadDistribution.Count / totalPersonnel;\\r\\n\\r\\n            _logger.LogInformation(\\\"📈 工作负载分析 - 平均：{Avg:F2}，最大：{Max}，最小：{Min}，人员利用率：{Util:P2}，基尼系数：{Gini:F4}\\\", \\r\\n                avgWorkload, maxWorkload, minWorkload, utilizationRate, CalculateGiniCoefficient(workloads));\\r\\n\\r\\n            // 详细分布统计\\r\\n            var distributionLog = string.Join(\\\", \\\", \\r\\n                workloadDistribution.OrderBy(kv => kv.Key)\\r\\n                                  .Select(kv => $\\\"人员{kv.Key}:{kv.Value}任务\\\"));\\r\\n            \\r\\n            _logger.LogDebug(\\\"📊 详细负载分布：{Distribution}\\\", distributionLog);\\r\\n        }\\r\\n\\r\\n        #endregion\\r\\n\\r\\n        #region ShiftRuleValidationEngine集成辅助方法\\r\\n\\r\\n        /// <summary>\\r\\n        /// 【深度实现】构建ShiftRuleValidationEngine所需的验证上下文\\r\\n        /// 【业务思考】：模拟当前批次中其他可能的人员分配，为班次规则验证提供完整的上下文信息\\r\\n        /// 【技术难点】：需要从决策变量中推断出可能的分配结果，构建验证所需的WorkOrderEntity列表\\r\\n        /// </summary>\\r\\n        private List<WorkOrderEntity> BuildValidationContext(\\r\\n            long targetPersonnelId, \\r\\n            long targetTaskId, \\r\\n            GlobalAllocationContext context,\\r\\n            Dictionary<(long TaskId, long PersonnelId), Variable> decisionVars)\\r\\n        {\\r\\n            var validationContext = new List<WorkOrderEntity>();\\r\\n            \\r\\n            try\\r\\n            {\\r\\n                // 【上下文构建策略1】添加同一人员的其他高概率分配任务\\r\\n                // 基于预筛选结果找到该人员其他可能的任务分�?\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.3}}"}}
{"timestamp":"2025-09-22T13:28:44.776Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:28:46.637Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Continuing review**"}}
{"timestamp":"2025-09-22T13:28:47.894Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":167071,"cached_input_tokens":145920,"output_tokens":1726,"reasoning_output_tokens":832,"total_tokens":168797},"last_token_usage":{"input_tokens":23874,"cached_input_tokens":21760,"output_tokens":77,"reasoning_output_tokens":0,"total_tokens":23951},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:28:47.894Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Continuing review**"}],"content":null,"encrypted_content":"gAAAAABo0U8PIunzEeGYDeLhVtKqK3J7KOh6ru0ObuviGn_l9rtv3-4XN4KVgl04xkahO_WTHdivTIEr-UyGSobfXvCrocNlnZIVqB8ZpDgVFfOJcFpkZCksKli7gwQK2_ZL0eoZS72atceeylELIHqoIZg_57h0GMBjzd8NhvHtaYOYYRDpXii26toYMZdmPMOW3c6WuTZ7abim6wBK6qZDr-iGYHdpy2kJzQulODP8JjJrB95WCxJUatlRbvkZT0L_6L2JinFD1-x3rarq4eGfBMoVrOnezDjOoIh7A5h14TEBLiUfmCwF-pkVdjTr2h1B9S_nNO4GaynYpZRTl2xy3Th9tQZOA1ceJqs2fGbw1rKdyp3CWsfTwW1wsDYiGHkz7yO11wLLaVdbzra69GhLm26Dg6MGvqMiNZQpsVhk2yIX0B_JWXdnkWARcoDROVCPV2PXQGSlol-wN0fbdw07CCRxWfm5Kgx6EsR2NXjCSYiIm3tsqauCuCpNMD4IbI1eAsSh6sPDtNi8KYHy_26FAM5xjhcqCtCIpLf8vCN4jKOl_TtSqNLz0jIMKc2H5WXphvaoRC7H2jTul3v5wi1T6K874SavIo1gZApTljJuSMSz8bwgJVRKUxrOXtwU61rcjWq4Oi_iBYE8jtelStfoKg8XfHqhrSLNFeboun5O9kkjCNMwffUk4whnvXaHjPvjIqpT6uu15C6RoNsyLZMOMw0WamhVWzhHcAfcIgJghOCLQD-WnR67yxZe45qYCTd-lQlRtfGwxJ4TOuF17SRdCl-o6vzPPF79j7P2kqDhtospKphEBAsE9mHWIiTCG4D7Q8kVsSNhpUTNeD2GOJvyjvUg1NBxdD9ocTn3lADcLOXZ476Uq6iCzWUIaLlmBAHzJn4J4tKp"}}
{"timestamp":"2025-09-22T13:28:47.894Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"Get-Content \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\" | Select-Object -Skip 1260 -First 160\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_BUjNpSKFGBJ9cAdojzWhOhxF"}}
{"timestamp":"2025-09-22T13:28:47.894Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_BUjNpSKFGBJ9cAdojzWhOhxF","output":"{\"output\":\"                foreach (var task in context.Tasks.Where(t => t.Id != targetTaskId))\\r\\n                {\\r\\n                    var prefilterKey = $\\\"{task.Id}_{targetPersonnelId}\\\";\\r\\n                    if (context.PrefilterResults.TryGetValue(prefilterKey, out var prefilterResult))\\r\\n                    {\\r\\n                        // 高评分或标记为可行的任务加入验证上下�?\\r\\n                        if (prefilterResult.IsFeasible || prefilterResult.PrefilterScore > 70.0)\\r\\n                        {\\r\\n                            var contextTask = task.CloneForValidation();\\r\\n                            contextTask.AssignedPersonnelId = targetPersonnelId; // 模拟分配\\r\\n                            validationContext.Add(contextTask);\\r\\n                        }\\r\\n                    }\\r\\n                }\\r\\n                \\r\\n                // 【上下文构建策略2】添加已确定分配的任务（来自历史数据�?\\r\\n                context.PersonnelHistoryTasks.TryGetValue(targetPersonnelId, out List<WorkOrderHistoryItem> historyTasks);\\r\\n                var existingAssignments = historyTasks.Where(t =>\\r\\n                        t.TaskId != targetTaskId)\\r\\n                    .ToList();\\r\\n                \\r\\n                foreach (var assignment in existingAssignments)\\r\\n                {\\r\\n                    validationContext.Add(new WorkOrderEntity()\\r\\n                    {\\r\\n                        Id = assignment.TaskId,\\r\\n                        WorkOrderDate = assignment.WorkDate,\\r\\n                        ShiftId = assignment.ShiftId,\\r\\n                        ShiftName = assignment.ShiftName,\\r\\n                        WorkOrderCode = assignment.TaskCode,\\r\\n                        ProjectNumber = assignment.ProjectNumber,\\r\\n                        Status = assignment.Status,\\r\\n                    });\\r\\n                }\\r\\n                \\r\\n                _logger.LogTrace(\\\"🔧 为人员{PersonnelId}任务{TaskId}构建验证上下文：{ContextSize}个任�?, \\r\\n                    targetPersonnelId, targetTaskId, validationContext.Count);\\r\\n                    \\r\\n                return validationContext;\\r\\n            }\\r\\n            catch (Exception ex)\\r\\n            {\\r\\n                _logger.LogError(ex, \\\"💥 构建验证上下文异常：人员{PersonnelId}任务{TaskId}\\\", targetPersonnelId, targetTaskId);\\r\\n                return new List<WorkOrderEntity>(); // 返回空上下文，保证验证能够继�?\\r\\n            }\\r\\n        }\\r\\n\\r\\n        #endregion\\r\\n\\r\\n        #region 辅助方法\\r\\n\\r\\n        /// <summary>\\r\\n        /// 【深度实现】判断是否为二班或三�?- 集成ShiftService的专业班次信息查�?\\r\\n        /// 【业务思考】：不再依赖简单的字符串匹配，而是通过ShiftService获取准确的班次信�?\\r\\n        /// 【性能优化】：添加班次信息缓存，避免重复的数据库查�?\\r\\n        /// </summary>\\r\\n        private Task<bool> IsSecondOrThirdShift(WorkOrderEntity task)\\r\\n        {\\r\\n            if (!task.ShiftId.HasValue) return Task.FromResult(false);\\r\\n            \\r\\n            try\\r\\n            {\\r\\n                // 【深度实现】使用已加载的ShiftEntity数据，避免额外的数据库查�?\\r\\n                var shift = task.ShiftEntity;\\r\\n                if (shift == null)\\r\\n                {\\r\\n                    _logger.LogWarning(\\\"⚠️ 无法获取班次{ShiftId}的信�?, task.ShiftId.Value);\\r\\n                    return Task.FromResult(false);\\r\\n                }\\r\\n                \\r\\n                // 【业务逻辑】多种判断方式确保准确�?\\r\\n                // 方法1：基于班次编�?\\r\\n                if (shift != null)\\r\\n                {\\r\\n                    return Task.FromResult(shift.ShiftNumber == 2 || shift.ShiftNumber == 3);\\r\\n                }\\r\\n                \\r\\n                // 方法2：基于班次名�?\\r\\n                if (!string.IsNullOrEmpty(shift?.Name))\\r\\n                {\\r\\n                    return Task.FromResult(shift.Name.Contains(\\\"二班\\\") || shift.Name.Contains(\\\"三班\\\") || \\r\\n                           shift.Name.Contains(\\\"中班\\\") || shift.Name.Contains(\\\"夜班\\\"));\\r\\n                }\\r\\n                \\r\\n                // 方法3：基于时间段（中班通常14:00-22:00，夜班通常22:00-06:00�?\\r\\n                if (shift != null)\\r\\n                {\\r\\n                    var startHour = shift.StartTime.Hours;\\r\\n                    return Task.FromResult(startHour >= 14 || startHour <= 6); // 14点后�?点前开始的班次\\r\\n                }\\r\\n                \\r\\n                return Task.FromResult(false);\\r\\n            }\\r\\n            catch (Exception ex)\\r\\n            {\\r\\n                _logger.LogError(ex, \\\"💥 判断班次类型异常：任务{TaskCode}班次{ShiftId}\\\", \\r\\n                    task.WorkOrderCode, task.ShiftId);\\r\\n                \\r\\n                // 【容错处理】异常情况下基于任务代码的启发式判断\\r\\n                return Task.FromResult(task.WorkOrderCode?.Contains(\\\"_2_\\\") == true || task.WorkOrderCode?.Contains(\\\"_3_\\\") == true);\\r\\n            }\\r\\n        }\\r\\n\\r\\n        /// <summary>\\r\\n        /// 【深度实现】估算人员技能等�?- 基于多维度数据的智能评估\\r\\n        /// 【业务思考】：通过人员资质、历史任务复杂度、工作经验等多个维度综合评估技能等�?\\r\\n        /// 【算法设计】：避免简单哈希，采用真实业务数据驱动的评估逻辑\\r\\n        /// </summary>\\r\\n        private int EstimatePersonnelLevel(long personnelId)\\r\\n        {\\r\\n            try\\r\\n            {\\r\\n                // 【维�?】基于人员资质数量和等级\\r\\n                var qualificationScore = CalculateQualificationScore(personnelId);\\r\\n                \\r\\n                // 【维�?】基于历史任务复杂度\\r\\n                var experienceScore = CalculateExperienceScore(personnelId);\\r\\n                \\r\\n                // 【维�?】基于工作年限（简化实现）\\r\\n                var seniorityScore = CalculateSeniorityScore(personnelId);\\r\\n                \\r\\n                // 【综合评分】加权计算最终技能等�?\\r\\n                var totalScore = qualificationScore * 0.4 + experienceScore * 0.4 + seniorityScore * 0.2;\\r\\n                \\r\\n                // 【等级映射】将评分映射�?-5�?\\r\\n                var level = totalScore switch\\r\\n                {\\r\\n                    >= 80 => 5, // 专家�?\\r\\n                    >= 65 => 4, // 高级\\r\\n                    >= 50 => 3, // 中级\\r\\n                    >= 30 => 2, // 初级\\r\\n                    _ => 1      // 新手\\r\\n                };\\r\\n                \\r\\n                _logger.LogTrace(\\\"📊 人员{PersonnelId}技能等级评估：资质{QualScore}+经验{ExpScore}+资历{SenScore}={TotalScore}→等级{Level}\\\", \\r\\n                    personnelId, qualificationScore, experienceScore, seniorityScore, totalScore, level);\\r\\n                    \\r\\n                return level;\\r\\n            }\\r\\n            catch (Exception ex)\\r\\n            {\\r\\n                _logger.LogError(ex, \\\"💥 人员技能等级评估异常：{PersonnelId}\\\", personnelId);\\r\\n                return 3; // 异常情况返回中级水平\\r\\n            }\\r\\n        }\\r\\n        \\r\\n        /// <summary>\\r\\n        /// 【深度实现】计算资质评分（0-100�?- 基于真实人员资质数据\\r\\n        /// 【业务思考】：根据人员的资质数量、级别、有效性等多维度计算评�?\\r\\n        /// 【算法设计】：资质数量(40%) + 高级资质加权(35%) + 有效�?25%)\\r\\n        /// </summary>\\r\\n        private double CalculateQualificationScore(long personnelId)\\r\\n        {\\r\\n            try\\r\\n            {\\r\\n                // 【数据获取】从上下文缓存中获取人员资质信息\\r\\n                // 注意：在线性规划优化过程中，上下文不可用，使用简化策�?\\r\\n                // 实际项目中应该传入GlobalAllocationContext作为参数\\r\\n                \\r\\n                // 【策�?】基于人员ID的现实数据特�?\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.3}}"}}
{"timestamp":"2025-09-22T13:28:47.894Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:28:49.585Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Continuing exploration**"}}
{"timestamp":"2025-09-22T13:28:50.421Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":192983,"cached_input_tokens":169728,"output_tokens":1803,"reasoning_output_tokens":832,"total_tokens":194786},"last_token_usage":{"input_tokens":25912,"cached_input_tokens":23808,"output_tokens":77,"reasoning_output_tokens":0,"total_tokens":25989},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:28:50.421Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Continuing exploration**"}],"content":null,"encrypted_content":"gAAAAABo0U8StJR6mDs5YXbl2GgpDmmZSByH7e4n631R-mqXk1xM9ydiRWFztX5T_2QN3k-704_iTw5uG0PJe0zk-RhToQ8doXGoMK4LaN5Ul4e573qmcrOWgjuM-NhaekSFXnNvstoK65jYW42G5WjsehKDzjFtF1owP_r6mRiqHVirbx6RjGf_Z4oQfJfRb4mwOhuvWe40MMWNtXImKD3tE0FgV0sKDTtU1GgDsFwZmRWz_UGQU1Px7lEmeANzE2XoP8K1UyMgnLW7U7XkeWNmuX0k8DuGDUAzvDgcg94Q0W1ntCC2Ey4HGxCfdaOoaYbmJn_QZSvQbnl0jt553t8mUYkrl-iBugT26ZPAHsG7v00YjewaXbYAKNIJSeUL0oDeUIlD2oaKfwrJPX86YTDHDEpBhPwIUnr_J5VYlQebXfG9akjPUZW3bV2ZBJYz9opi-fFyzqjvJEBCWmznjO8dcXwrcP8D7m1WXRGdhw3eZ1Z9OQk7vEQcEIVXArYJQOAdhdj54C-_lJcOh_64sulOthBnVt7ropH-HkKuJLSJC0eIW-lWF5vF2Zu1fuv76Y8-R9YmXPWvyIs9ApJV-U58NsZj8RCVb3k5oMQYcjqC1A_h9olOCSG6X1OeguG1E4GSbHOOtwmug-01cLOM50xC1naZUGwPMkI4XA4SmnfVGzHDIBVzt-Rujob7amVX9VxJ7whBSPkO4-NFWLvONiU9NdNzdlKKdfXgkpxgC491UMpNgztvATiGZ7kFpDtBC4THOjfuMQNIjdq66rfB_rUKwbWijIL4ecU_7xeQGbY0GiDNeWG5xhgvZI__jXxdB5UxQ3y0hsIpSBeQjSYAq64rXITfNGFOl6SL_8IGEWcae8uCzF8VS9E="}}
{"timestamp":"2025-09-22T13:28:50.421Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"Get-Content \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\" | Select-Object -Skip 1420 -First 160\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_T8Qwk5uGyCItOB5HkC3QurLY"}}
{"timestamp":"2025-09-22T13:28:50.421Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_T8Qwk5uGyCItOB5HkC3QurLY","output":"{\"output\":\"                var baseScore = 50.0; // 基础�?\\r\\n                \\r\\n                // 【特征提取】从人员ID中提取数值特�?\\r\\n                var idValue = personnelId;\\r\\n                \\r\\n                // 【资质数量估算】基于ID数值模拟资质数�?1-8个资�?\\r\\n                var qualificationCount = (int)(idValue % 8) + 1;\\r\\n                var quantityScore = Math.Min(qualificationCount * 8.0, 40.0); // 最�?0�?\\r\\n                \\r\\n                // 【高级资质加权】模拟高级资质持有情�?\\r\\n                var hasAdvancedQualifications = (idValue % 3) == 0; // 1/3的人员拥有高级资�?\\r\\n                var advancedScore = hasAdvancedQualifications ? 35.0 : 15.0;\\r\\n                \\r\\n                // 【有效性检查】模拟资质有效性（基于时间因子�?\\r\\n                var validityScore = (idValue % 10) > 2 ? 25.0 : 10.0; // 80%的资质有�?\\r\\n                \\r\\n                var totalScore = baseScore + quantityScore + advancedScore + validityScore;\\r\\n                \\r\\n                _logger.LogTrace(\\\"【资质评分计算】人员{PersonnelId}：基础{Base}+数量{Qty}+高级{Adv}+有效{Valid}={Total}\\\",\\r\\n                    personnelId, baseScore, quantityScore, advancedScore, validityScore, totalScore);\\r\\n                    \\r\\n                return Math.Min(totalScore, 100.0); // 保证不超�?00�?\\r\\n            }\\r\\n            catch (Exception ex)\\r\\n            {\\r\\n                _logger.LogError(ex, \\\"【资质评分计算异常】人员{PersonnelId}\\\", personnelId);\\r\\n                return 50.0; // 异常情况返回中等水平\\r\\n            }\\r\\n        }\\r\\n        \\r\\n        /// <summary>\\r\\n        /// 【深度实现】计算经验评分（0-100�?- 基于任务歷史数据分析\\r\\n        /// 【业务思考】：通过分析人员的历史任务复杂度、完成质量、任务类型多样性评估经�?\\r\\n        /// 【算法设计】：任务数量(30%) + 复杂度经�?40%) + 完成质量(30%)\\r\\n        /// </summary>\\r\\n        private double CalculateExperienceScore(long personnelId)\\r\\n        {\\r\\n            try\\r\\n            {\\r\\n                // 【经验数据分析】基于人员ID的数值特征分�?\\r\\n                var idValue = personnelId;\\r\\n                \\r\\n                // 【任务数量经验】估算历史任务数�?10-200个任�?\\r\\n                var taskCount = (int)(idValue % 190) + 10;\\r\\n                var taskCountScore = Math.Min(taskCount / 6.0, 30.0); // �?个任务计�?分，最�?0�?\\r\\n                \\r\\n                // 【复杂度经验】基于人员特征估算复杂任务处理经�?\\r\\n                var complexityFactor = (idValue % 7) + 1; // 1-7的复杂度系数\\r\\n                var complexityScore = Math.Min(complexityFactor * 5.5, 40.0); // 最�?0�?\\r\\n                \\r\\n                // 【完成质量】模拟任务完成质量评估（85%-98%的成功率�?\\r\\n                var successRate = 0.85 + (idValue % 14) * 0.01; // 85%-98%的成功率\\r\\n                var qualityScore = successRate * 30.0; // 最�?0�?\\r\\n                \\r\\n                // 【经验加权】资深人员额外加�?\\r\\n                var seniorityBonus = (idValue % 5) == 0 ? 10.0 : 0.0; // 20%的人员获得资深加�?\\r\\n                \\r\\n                var totalScore = taskCountScore + complexityScore + qualityScore + seniorityBonus;\\r\\n                \\r\\n                _logger.LogTrace(\\\"【经验评分计算】人员{PersonnelId}：任务{Task}+复杂度{Complex}+质量{Quality}+加分{Bonus}={Total}\\\",\\r\\n                    personnelId, taskCountScore, complexityScore, qualityScore, seniorityBonus, totalScore);\\r\\n                    \\r\\n                return Math.Min(totalScore, 100.0);\\r\\n            }\\r\\n            catch (Exception ex)\\r\\n            {\\r\\n                _logger.LogError(ex, \\\"【经验评分计算异常】人员{PersonnelId}\\\", personnelId);\\r\\n                return 60.0; // 异常情况返回中等以上水平\\r\\n            }\\r\\n        }\\r\\n        \\r\\n        /// <summary>\\r\\n        /// 【深度实现】计算资历评分（0-100�?- 基于工作年限和职业发�?\\r\\n        /// 【业务思考】：综合考虑工作年限、职位等级、行业经验等因素\\r\\n        /// 【算法设计】：工作年限(50%) + 职位等级(30%) + 行业经验(20%)\\r\\n        /// </summary>\\r\\n        private double CalculateSeniorityScore(long personnelId)\\r\\n        {\\r\\n            try\\r\\n            {\\r\\n                // 【资历数据分析】基于人员ID的数值特征分�?\\r\\n                var idValue = personnelId;\\r\\n                \\r\\n                // 【工作年限】估算工作年�?1-25�?\\r\\n                var workingYears = (int)(idValue % 25) + 1;\\r\\n                \\r\\n                // 年限评分：新�?1-2�?、经�?3-8�?、资�?9-15�?、专�?16+�?\\r\\n                var yearsScore = workingYears switch\\r\\n                {\\r\\n                    <= 2 => 15.0,    // 新手�?\\r\\n                    <= 8 => 25.0,    // 经验�?\\r\\n                    <= 15 => 40.0,   // 资深�?\\r\\n                    _ => 50.0         // 专家�?\\r\\n                };\\r\\n                \\r\\n                // 【职位等级】模拟人员在组织中的职位级别\\r\\n                var positionLevel = (int)(idValue % 6) + 1; // 1-6�?\\r\\n                var positionScore = positionLevel * 5.0; // 每级1级加5分，最�?0�?\\r\\n                \\r\\n                // 【行业经验】模拟在相关行业的经�?\\r\\n                var industryExperience = (idValue % 4) == 0; // 25%的人员有丰富行业经验\\r\\n                var industryScore = industryExperience ? 20.0 : 10.0;\\r\\n                \\r\\n                var totalScore = yearsScore + positionScore + industryScore;\\r\\n                \\r\\n                _logger.LogTrace(\\\"【资历评分计算】人员{PersonnelId}：年限{Years}�?评分{YearsScore})+职位{Position}�?评分{PosScore})+行业经验({IndScore})={Total}\\\",\\r\\n                    personnelId, workingYears, yearsScore, positionLevel, positionScore, industryScore, totalScore);\\r\\n                    \\r\\n                return Math.Min(totalScore, 100.0);\\r\\n            }\\r\\n            catch (Exception ex)\\r\\n            {\\r\\n                _logger.LogError(ex, \\\"【资历评分计算异常】人员{PersonnelId}\\\", personnelId);\\r\\n                return 40.0; // 异常情况返回中等水平\\r\\n            }\\r\\n        }\\r\\n        \\r\\n        /// <summary>\\r\\n        /// 【简化实现】后备资质验�?- 基于ContextBuilderEngine的成熟实�?\\r\\n        /// 【设计理念】：复用ContextBuilderEngine的CheckQualificationRequirementsAsync逻辑\\r\\n        /// 【使用场景】：仅当预筛选结果不可用时的安全保障机制\\r\\n        /// </summary>\\r\\n        private async Task<bool> CheckQualificationCompatibilityAsync(long taskId, long personnelId, GlobalAllocationContext context)\\r\\n        {\\r\\n            try\\r\\n            {\\r\\n                // 获取任务和人员信�?\\r\\n                var task = context.Tasks.FirstOrDefault(t => t.Id == taskId);\\r\\n                var personnel = context.AvailablePersonnel.FirstOrDefault(p => p.Id == personnelId);\\r\\n                \\r\\n                if (task == null || personnel == null)\\r\\n                {\\r\\n                    _logger.LogWarning(\\\"⚠️ 后备资质验证失败 - 任务{TaskId}或人员{PersonnelId}不存�?, taskId, personnelId);\\r\\n                    return false;\\r\\n                }\\r\\n                \\r\\n                // 【步�?】检查缓存中的人员资质数�?\\r\\n                if (!context.PersonnelQualificationsCache.TryGetValue(personnelId, out var qualifications))\\r\\n                {\\r\\n                    _logger.LogTrace(\\\"�?后备资质验证 - 人员{PersonnelId}无资质缓存数�?, personnelId);\\r\\n                    return false;\\r\\n                }\\r\\n                \\r\\n                // 【步�?】筛选有效资质（参考ContextBuilderEngine实现�?\\r\\n                var currentTime = DateTime.Now;\\r\\n                var validQualifications = qualifications.Where(q => \\r\\n                    q.IsActive && // 资质必须处于激活状�?\\r\\n                    (q.ExpiryDate == null || q.ExpiryDate > currentTime) // 资质必须在有效期�?\\r\\n                ).ToList();\\r\\n                \\r\\n                if (!validQualifications.Any())\\r\\n                {\\r\\n                    _logger.LogTrace(\\\"�?后备资质验证 - 人员{PersonnelId}无有效资�?, personnelId);\\r\\n                    return false;\\r\\n                }\\r\\n                \\r\\n                // 【步�?】检查任务资质要求（简化版�?\\r\\n                if (!string.IsNullOrWhiteSpace(task.ProcessEntity?.QualificationRequirements))\\r\\n                {\\r\\n                    // 解析任务资质要求\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.3}}"}}
{"timestamp":"2025-09-22T13:28:50.421Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:28:52.310Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Continuing task progress**"}}
{"timestamp":"2025-09-22T13:28:53.310Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":221314,"cached_input_tokens":195584,"output_tokens":1880,"reasoning_output_tokens":832,"total_tokens":223194},"last_token_usage":{"input_tokens":28331,"cached_input_tokens":25856,"output_tokens":77,"reasoning_output_tokens":0,"total_tokens":28408},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:28:53.310Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Continuing task progress**"}],"content":null,"encrypted_content":"gAAAAABo0U8V0B9tLmyCK6VjaH1F7eOgS1Rsy1awPfjltKAjPfw_6P9BriRHUdF9EUSHG28cr6rfPpr1hrtGtrtZQk7mZn13NFcTAbAgzll7FSOf8Hi71KWJJsAYlVQUNc2lbi6KD9RTQRO6DuPhmcZ1h-KfpIT9mWUIogLI3qHWVVkO4hlcB9v3QPMMh2HnvqhCdXhpZf8D1K8-r2h0ECFTkMFXyyg7r91nXgfR5WA2ZERrw_NHfCUSXohQLtxk3rP2ZIAKvRjYdp6violT0tX-AkmWfYgxH3_Sv-GYrrSBvl4LhvhwS6YbTDH_QIagWT_0y-GvaO_wxTZ-GttdGwK0FaImaCucKSDjBVuayim9M8JTIPFI3DD0stWF0WJebBSFyN2pzHq-q02f7NdNHWciA46hCYLRLvc8QUPqjBU7jzTqYiZVaa2vdbiJ4GXKPU5vg2p2il-XbDgv38H8T6HHAvTnM1MjqMdWUud_JZ0PfDuu1uJoiVTXYUr7zjRnv4S4X1Hmk1ggVPMWIA2PG8zqEJRYIODSGNehU1QuJ2GEHooxDRV-6Kn_rIitKhZyiBBzBNHiJOB-psD_6jR_JVzldb1LKZUVPXDfxKGsdtWUmjedjlUOVYi9UGKo6vJa31ZRzTgVDcIA4cV0_EucolZJqztzhuTXzU8Y--V28hPVJxCjZttTUBIKAhcwgZRMP8J9neZ3TtKnG6pfGADWP0WcPGzBfpq2_jUg1Yw0oBOnoiyRyihiH82VwAg1dNjAOHnuLwNuk8mq_0T7P4qU11eZt6uGpTBIEvztKuOJg3oLXTqaxEKrwwccmEYx3hHdeHuTgDgu7Lj4ySwuaAx1R44o8PcGYH6Ia1m39GRym21UjbBz2sZyV88="}}
{"timestamp":"2025-09-22T13:28:53.310Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"Get-Content \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\" | Select-Object -Skip 1580 -First 160\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_hczoK4VKq3S0N9RqpK3Q5Qso"}}
{"timestamp":"2025-09-22T13:28:53.310Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_hczoK4VKq3S0N9RqpK3Q5Qso","output":"{\"output\":\"                    var requiredQualificationIds = task.ProcessEntity.QualificationRequirements\\r\\n                        .Split(',', StringSplitOptions.RemoveEmptyEntries)\\r\\n                        .Select(q => q.Trim())\\r\\n                        .Where(q => long.TryParse(q, out _))\\r\\n                        .Select(q => long.Parse(q))\\r\\n                        .ToHashSet();\\r\\n                    \\r\\n                    // 检查人员是否具备任一所需资质\\r\\n                    var personnelQualificationIds = validQualifications.Select(q => q.QualificationId).ToHashSet();\\r\\n                    var hasRequiredQualification = requiredQualificationIds.Any(rq => personnelQualificationIds.Contains(rq));\\r\\n                    \\r\\n                    if (!hasRequiredQualification)\\r\\n                    {\\r\\n                        _logger.LogTrace(\\\"�?后备资质验证 - 人员{PersonnelId}不具备任务{TaskId}所需资质\\\", personnelId, taskId);\\r\\n                        return false;\\r\\n                    }\\r\\n                }\\r\\n                \\r\\n                // 【步�?】检查岗位负责人要求（简化版�?\\r\\n                if (task.NeedPostHead)\\r\\n                {\\r\\n                    var hasHighLevelQualification = validQualifications.Any(q => q.HighLevel);\\r\\n                    if (!hasHighLevelQualification)\\r\\n                    {\\r\\n                        _logger.LogTrace(\\\"�?后备资质验证 - 任务{TaskId}需要岗位负责人，但人员{PersonnelId}无高级别资质\\\", taskId, personnelId);\\r\\n                        return false;\\r\\n                    }\\r\\n                }\\r\\n                \\r\\n                return true; // 通过所有验�?\\r\\n            }\\r\\n            catch (Exception ex)\\r\\n            {\\r\\n                _logger.LogError(ex, \\\"💥 后备资质验证异常 - 任务{TaskId}人员{PersonnelId}\\\", taskId, personnelId);\\r\\n                return false; // 异常时保守处�?\\r\\n            }\\r\\n        }\\r\\n        \\r\\n\\r\\n        /// <summary>\\r\\n        /// 检查技能匹�?\\r\\n        /// </summary>\\r\\n        private bool IsSkillMatched(decimal taskComplexity, int personnelLevel)\\r\\n        {\\r\\n            return taskComplexity switch\\r\\n            {\\r\\n                <= 2 => true,\\r\\n                <= 4 => personnelLevel >= 2,\\r\\n                _ => personnelLevel >= 3\\r\\n            };\\r\\n        }\\r\\n\\r\\n        /// <summary>\\r\\n        /// 从工单编码提取项目标�?\\r\\n        /// </summary>\\r\\n        private string ExtractProjectFromWorkOrderCode(string workOrderCode)\\r\\n        {\\r\\n            if (string.IsNullOrEmpty(workOrderCode)) return \\\"unknown\\\";\\r\\n            \\r\\n            var parts = workOrderCode.Split('_');\\r\\n            return parts.Length > 0 ? parts[0] : workOrderCode;\\r\\n        }\\r\\n\\r\\n        /// <summary>\\r\\n        /// 【简化实现】计算技能匹配奖励分�?- 基于预筛选结�?\\r\\n        /// 【架构优化】：直接使用预筛选阶段的专业评估结果，避免重复计�?\\r\\n        /// 【性能提升】：从复杂的多维度评估简化为单一缓存查询\\r\\n        /// </summary>\\r\\n        private double CalculateSkillMatchingBonus(WorkOrderEntity task, long personnelId, GlobalAllocationContext context)\\r\\n        {\\r\\n            // 【核心简化】使用预筛选结果中的评分作为技能匹配依�?\\r\\n            var prefilterKey = $\\\"{task.Id}_{personnelId}\\\";\\r\\n            \\r\\n            if (context.PrefilterResults.TryGetValue(prefilterKey, out var prefilterResult))\\r\\n            {\\r\\n                // 将预筛选评分转换为奖励分数\\r\\n                var baseBonus = (prefilterResult.PrefilterScore - 50.0) * 2.0; // 50分以上为正奖励，以下为负惩罚\\r\\n                \\r\\n                // 可行性额外奖�?\\r\\n                var feasibilityBonus = prefilterResult.IsFeasible ? 20.0 : -50.0;\\r\\n                \\r\\n                return Math.Max(-100.0, Math.Min(200.0, baseBonus + feasibilityBonus)); // 限制在[-100, 200]范围\\r\\n            }\\r\\n            \\r\\n            // 无预筛选数据时的保守评�?\\r\\n            return 0.0;\\r\\n        }\\r\\n\\r\\n        /// <summary>\\r\\n        /// 计算分配评分\\r\\n        /// </summary>\\r\\n        private double CalculateAssignmentScore(long taskId, long personnelId, GlobalAllocationContext context)\\r\\n        {\\r\\n            var prefilterKey = $\\\"{taskId}_{personnelId}\\\";\\r\\n            var baseScore = 100.0;\\r\\n            \\r\\n            if (context.PrefilterResults.TryGetValue(prefilterKey, out var result))\\r\\n            {\\r\\n                baseScore = result.PrefilterScore;\\r\\n            }\\r\\n            \\r\\n            var task = context.Tasks.FirstOrDefault(t => t.Id == taskId);\\r\\n            if (task != null)\\r\\n            {\\r\\n                baseScore += CalculateSkillMatchingBonus(task, personnelId, context);\\r\\n            }\\r\\n            \\r\\n            return baseScore;\\r\\n        }\\r\\n\\r\\n        /// <summary>\\r\\n        /// 计算基尼系数\\r\\n        /// </summary>\\r\\n        private double CalculateGiniCoefficient(List<decimal> values)\\r\\n        {\\r\\n            if (!values.Any()) return 0;\\r\\n\\r\\n            var n = values.Count;\\r\\n            var sortedValues = values.OrderBy(x => x).ToArray();\\r\\n\\r\\n            double numerator = 0;\\r\\n            for (int i = 0; i < n; i++)\\r\\n            {\\r\\n                numerator += (2 * (i + 1) - n - 1) * (double)sortedValues[i];\\r\\n            }\\r\\n\\r\\n            var mean = values.Average(x => (double)x);\\r\\n            return mean == 0 ? 0 : numerator / (n * n * mean);\\r\\n        }\\r\\n\\r\\n        /// <summary>\\r\\n        /// 创建失败解决方案\\r\\n        /// </summary>\\r\\n        private GlobalOptimizedSolution CreateFailureSolution(string errorMessage, long elapsedMs)\\r\\n        {\\r\\n            return new GlobalOptimizedSolution\\r\\n            {\\r\\n                BestSolution = new Dictionary<long, long>(),\\r\\n                BestFitness = 0.0,\\r\\n                ActualGenerations = 0,\\r\\n                ConstraintSatisfactionRate = 0.0\\r\\n            };\\r\\n        }\\r\\n\\r\\n        #endregion\\r\\n\\r\\n        #region 增强版批次感知验证支持方�?\\r\\n\\r\\n        /// <summary>\\r\\n        /// 【Ultra think核心方法】执行批次感知验�?- 真正解决当前分配组合+历史验证问题\\r\\n        /// 【深度业务思考】：对每个人员的所有可能任务组合进行交叉验�?\\r\\n        /// 【架构创新】：从单任务+历史模式升级为批次组�?历史的全面验证模�?\\r\\n        /// </summary>\\r\\n        private async Task<Dictionary<long, List<string>>> ExecuteBatchAwareValidationAsync(\\r\\n            long personnelId,\\r\\n            List<WorkOrderEntity> possibleTasks,\\r\\n            GlobalAllocationContext context,\\r\\n            PersonnelTaskMatrix matrix)\\r\\n        {\\r\\n            var validationResults = new Dictionary<long, List<string>>();\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.3}}"}}
{"timestamp":"2025-09-22T13:28:53.311Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:28:54.862Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Continuing exploration**"}}
{"timestamp":"2025-09-22T13:28:55.979Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":251472,"cached_input_tokens":223872,"output_tokens":1957,"reasoning_output_tokens":832,"total_tokens":253429},"last_token_usage":{"input_tokens":30158,"cached_input_tokens":28288,"output_tokens":77,"reasoning_output_tokens":0,"total_tokens":30235},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:28:55.979Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Continuing exploration**"}],"content":null,"encrypted_content":"gAAAAABo0U8XGlkrbbgh60bXU_FgNZckjCVoPnjCm1KQN1rTP99OKWW8Yy0DAQLgFvvCkhifbVHY74w0UTN91SOnNzWPAqHbUy6jIsmAWxf06Pkp98cFkv5-7hVof65W3v_4htJdjO68amcnG_28W5uBEE5YSU1X49pCs-vJJYXReYLHFTWScFaJpCc-VO5ICktuSkKlFNGL5ANOeKJS-DAkth8_Dz435Zc68zn_VUtlVeoNsMP94E7v7WpkmYNLeDGPnzl11JjC8l1H0egi9iZxsRoDow9nZyCRJAolmaC6qNjlgjcKfZJ1CfwcwYN0EJ3NoV1NnS6Fdu6BRnUYHF7_aAHpscKiiRboZKameSlwdS4evcftPF6ODHe7Fc0gQINAaZDOsAN8ZlCZtyUbJ4Je05MwrBZiTITg0s7-2IqxoQDvFCzQ43RlLkVhnMAIKipFjEhIkqm2dHz8tKT6VsHISRJoncMkYeuhO7DvsSrjwIe4qGnEYVjO7_PKutmOhNA7ObULEqhCId7ul2EbsoRvWY3uej8FQ4zTvSxBBAXTbNyoPc2t5UIbmqEdKsIgMVBC7Mmy7Rs_ZeotUHKw5Uwr2ty2AKWi2vhIq6EDzAKKpMkcNI6Aj4ggQftWBEz1QQMUfmVaOJ39sSyTHPqLyABGNudYpDbsZgpn3IYQEez5Z0IviC1fckIdrih8rykho7n4v6vpvnMtFBbntaM0H3LLD-G0q9OKIG_GiGoh0ev162HoV55lxdDb1tbLv7mDx7kcg4AGYhyMqZtLHZQSC0DIMh7f_APSsHW4mKU09m6DahZuwco5EES65FSIdNQX884wLOKGjicm41G7kvNQhziTdscX-TfHJK1ZCo2yMx_koLJGbjvB_1w="}}
{"timestamp":"2025-09-22T13:28:55.979Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"Get-Content \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\" | Select-Object -Skip 1740 -First 160\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_TDxAlj1BS3kLVAYdiqyh2o7H"}}
{"timestamp":"2025-09-22T13:28:55.980Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_TDxAlj1BS3kLVAYdiqyh2o7H","output":"{\"output\":\"            \\r\\n            try\\r\\n            {\\r\\n                // 【步�?】获取该人员的历史任务作为验证基�?\\r\\n                context.PersonnelHistoryTasks.TryGetValue(personnelId, out var historyTasks);\\r\\n                var baselineTasks = historyTasks?.Select(h => new WorkOrderEntity\\r\\n                {\\r\\n                    Id = h.TaskId,\\r\\n                    WorkOrderDate = h.WorkDate,\\r\\n                    ShiftId = h.ShiftId,\\r\\n                    ShiftName = h.ShiftName,\\r\\n                    WorkOrderCode = h.TaskCode,\\r\\n                    ProjectNumber = h.ProjectNumber,\\r\\n                    Status = h.Status\\r\\n                }).ToList() ?? new List<WorkOrderEntity>();\\r\\n\\r\\n                // 【步�?】为每个可能的任务构建批次感知验证上下文\\r\\n                foreach (var candidateTask in possibleTasks)\\r\\n                {\\r\\n                    var violations = new List<string>();\\r\\n                    \\r\\n                    // 【核心创新】构建当前批次的模拟分配上下�?\\r\\n                    var batchSimulationContext = BuildBatchSimulationContext(\\r\\n                        personnelId, candidateTask, possibleTasks, baselineTasks, context);\\r\\n                        \\r\\n                    // 【批次验�?】检查与批次内其他任务的时间冲突\\r\\n                    var batchTimeConflicts = CheckBatchTimeConflicts(candidateTask, batchSimulationContext);\\r\\n                    if (batchTimeConflicts.Any())\\r\\n                    {\\r\\n                        violations.AddRange(batchTimeConflicts);\\r\\n                    }\\r\\n\\r\\n                    // 【批次验�?】使用ShiftRuleValidationEngine进行专业班次规则验证\\r\\n                    try\\r\\n                    {\\r\\n                        var conflicts = await _shiftRuleEngine.ValidateShiftRulesWithEnhancedBatchContextAsync(\\r\\n                            personnelId, candidateTask, batchSimulationContext, context);\\r\\n                        \\r\\n                        foreach (var conflict in conflicts)\\r\\n                        {\\r\\n                            violations.Add($\\\"班次规则冲突: {conflict}\\\");\\r\\n                        }\\r\\n                    }\\r\\n                    catch (Exception ex)\\r\\n                    {\\r\\n                        _logger.LogWarning(ex, \\\"⚠️ 批次感知班次规则验证异常 - 人员{PersonnelId}任务{TaskId}\\\", personnelId, candidateTask.Id);\\r\\n                        violations.Add($\\\"班次规则验证异常: {ex.Message}\\\");\\r\\n                    }\\r\\n\\r\\n                    // 【批次验�?】检查工作负载限�?\\r\\n                    var workloadViolations = CheckBatchWorkloadLimits(candidateTask, batchSimulationContext, personnelId);\\r\\n                    if (workloadViolations.Any())\\r\\n                    {\\r\\n                        violations.AddRange(workloadViolations);\\r\\n                    }\\r\\n\\r\\n                    // 【批次验�?】检查人员不可用性（基于班次不可用性缓存）\\r\\n                    var unavailabilityViolations = CheckPersonnelUnavailability(candidateTask, personnelId, context);\\r\\n                    if (unavailabilityViolations.Any())\\r\\n                    {\\r\\n                        violations.AddRange(unavailabilityViolations);\\r\\n                    }\\r\\n\\r\\n                    validationResults[candidateTask.Id] = violations;\\r\\n                    \\r\\n                    if (violations.Any())\\r\\n                    {\\r\\n                        _logger.LogTrace(\\\"🔍 批次感知验证 - 人员{PersonnelId}任务{TaskId}发现{ViolationCount}个问题：{Violations}\\\",\\r\\n                            personnelId, candidateTask.Id, violations.Count, string.Join(\\\"; \\\", violations.Take(3)));\\r\\n                    }\\r\\n                }\\r\\n\\r\\n                return validationResults;\\r\\n            }\\r\\n            catch (Exception ex)\\r\\n            {\\r\\n                _logger.LogError(ex, \\\"💥 批次感知验证异常 - 人员{PersonnelId}\\\", personnelId);\\r\\n                \\r\\n                // 异常情况下为所有任务返回错误标�?\\r\\n                foreach (var task in possibleTasks)\\r\\n                {\\r\\n                    validationResults[task.Id] = new List<string> { $\\\"批次验证异常: {ex.Message}\\\" };\\r\\n                }\\r\\n                return validationResults;\\r\\n            }\\r\\n        }\\r\\n\\r\\n        /// <summary>\\r\\n        /// 构建批次模拟上下�?- 模拟当前人员在批次中的完整任务分配情�?\\r\\n        /// </summary>\\r\\n        private List<WorkOrderEntity> BuildBatchSimulationContext(\\r\\n            long personnelId,\\r\\n            WorkOrderEntity candidateTask,\\r\\n            List<WorkOrderEntity> possibleTasks,\\r\\n            List<WorkOrderEntity> baselineTasks,\\r\\n            GlobalAllocationContext context)\\r\\n        {\\r\\n            var simulationContext = new List<WorkOrderEntity>();\\r\\n            \\r\\n            // 添加历史基线任务\\r\\n            simulationContext.AddRange(baselineTasks);\\r\\n            \\r\\n            // 【批次感知策略】添加其他高概率的批次任�?\\r\\n            foreach (var otherTask in possibleTasks)\\r\\n            {\\r\\n                if (otherTask.Id == candidateTask.Id) continue;\\r\\n                \\r\\n                var prefilterKey = $\\\"{otherTask.Id}_{personnelId}\\\";\\r\\n                if (context.PrefilterResults.TryGetValue(prefilterKey, out var prefilterResult))\\r\\n                {\\r\\n                    // 高评分或标记为可行的任务加入模拟上下�?\\r\\n                    if (prefilterResult.IsFeasible || prefilterResult.PrefilterScore > 60.0)\\r\\n                    {\\r\\n                        var simulatedTask = otherTask.CloneForValidation();\\r\\n                        simulatedTask.AssignedPersonnelId = personnelId;\\r\\n                        simulationContext.Add(simulatedTask);\\r\\n                    }\\r\\n                }\\r\\n            }\\r\\n            \\r\\n            return simulationContext;\\r\\n        }\\r\\n\\r\\n        /// <summary>\\r\\n        /// 检查批次时间冲�?- 与批次内其他任务的时间冲�?\\r\\n        /// </summary>\\r\\n        private List<string> CheckBatchTimeConflicts(\\r\\n            WorkOrderEntity candidateTask,\\r\\n            List<WorkOrderEntity> batchContext)\\r\\n        {\\r\\n            var violations = new List<string>();\\r\\n            \\r\\n            foreach (var existingTask in batchContext)\\r\\n            {\\r\\n                if (existingTask.Id == candidateTask.Id) continue;\\r\\n                \\r\\n                // 基础时间冲突检�?\\r\\n                if (existingTask.WorkOrderDate.Date == candidateTask.WorkOrderDate.Date &&\\r\\n                    existingTask.ShiftId == candidateTask.ShiftId)\\r\\n                {\\r\\n                    violations.Add($\\\"时间冲突: 与任务{existingTask.Id}在{candidateTask.WorkOrderDate:yyyy-MM-dd}班次{candidateTask.ShiftId}冲突\\\");\\r\\n                }\\r\\n                \\r\\n                // 扩展时间段重叠检�?\\r\\n                if (IsTimeSlotOverlap(existingTask, candidateTask))\\r\\n                {\\r\\n                    violations.Add($\\\"时间段重�? 与任务{existingTask.Id}存在时间段重�?);\\r\\n                }\\r\\n            }\\r\\n            \\r\\n            return violations;\\r\\n        }\\r\\n\\r\\n        /// <summary>\\r\\n        /// 检查批次工作负载限�?\\r\\n        /// </summary>\\r\\n        private List<string> CheckBatchWorkloadLimits(\\r\\n            WorkOrderEntity candidateTask,\\r\\n            List<WorkOrderEntity> batchContext,\\r\\n            long personnelId)\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.3}}"}}
{"timestamp":"2025-09-22T13:28:55.980Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:28:58.022Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Proceeding with task**"}}
{"timestamp":"2025-09-22T13:28:58.960Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":283421,"cached_input_tokens":253952,"output_tokens":2034,"reasoning_output_tokens":832,"total_tokens":285455},"last_token_usage":{"input_tokens":31949,"cached_input_tokens":30080,"output_tokens":77,"reasoning_output_tokens":0,"total_tokens":32026},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:28:58.960Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Proceeding with task**"}],"content":null,"encrypted_content":"gAAAAABo0U8buwLaOrrFXsQeGHws2JvE7RS8T5EpHY0yTw884dsUVMA6Lhao9eHkoVTAir1t6CnrO5IhTbUSnI4jFDWN9L2Jtq1Jr8l_exILFzU0es7FeH5SNy9JaLlA2OMgR57BL9LavcRTZAaz2-c7fiqsiE3xuM3yQKPf09flpk35jwsNve0Qe8rRnPVA6Svm64MGZCodyU9ED7Sw5T2KU9z7bjXTmPkj2cQVY3dn8rytsxHoRACPg6V3ea850cX8d4XXeBDtT_hHGtpD5xsOX38bfJR_m6sXezxb24oNTlvaDgYqb2RNRLnGsADZ2CrBiFCsKMe1jXbuWp8V3bdu5Hf-ypLNsQWze1xqk60t1mX3fOAf2322iKklg6U5poMFqOOIO2mJK90kI5CBx5GYNB322oTb0Wi7kRzt9S4d1R8-ZtGYZCoUvmFCIFeTtbnxnCgYJKyVZ8AECpOcGuzK1r-xo8rXcPPyFMIXJTJE3OmXktp3MPE_BlmDzQ0LQtac4y2AYrHWIfwSjQ2aqVa-d5iPAK1bolv-bB4QVVjocp9VIzBNGdwW8gOqz3P_pWZ_TMvFoR8RI_j_wx4yP2GX8QBykadCOJLKOm24wPk7CpURJBYn8OjIbH_atLgregm7H5sReX5LV1ySkqjP8_IFzC0LB9Bp1HNSlwW75WB4SBB_zbiD6iJqDwFPWbuGotRonD68zTiQ88mIS1uT0w1bBvjQreWsttAVdXy9Mw7mqyHHBuwuz44VBy0RNzZJKrxsJx97cQFvYRPXOGFm70Vvaeg9FAsWoHk9hwFgWkyi1WG1fHFqtH2lPm6TbNl64THdxFfapbHu1oacFrvPCoML_TsaEoODW2eyqrbkItvXjloEJefZjQE="}}
{"timestamp":"2025-09-22T13:28:58.960Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"Get-Content \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\" | Select-Object -Skip 1900 -First 160\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_8BrvTeD3v2ZnF7lkMYuXGiPH"}}
{"timestamp":"2025-09-22T13:28:58.960Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_8BrvTeD3v2ZnF7lkMYuXGiPH","output":"{\"output\":\"        {\\r\\n            var violations = new List<string>();\\r\\n            \\r\\n            // 按日期分组检查每日工作负�?\\r\\n            var dailyTasks = batchContext\\r\\n                .Where(t => t.AssignedPersonnelId == personnelId)\\r\\n                .GroupBy(t => t.WorkOrderDate.Date)\\r\\n                .ToList();\\r\\n                \\r\\n            // 检查候选任务所在日期的工作负载\\r\\n            var candidateDate = candidateTask.WorkOrderDate.Date;\\r\\n            var sameDayTasks = dailyTasks\\r\\n                .Where(g => g.Key == candidateDate)\\r\\n                .SelectMany(g => g)\\r\\n                .ToList();\\r\\n                \\r\\n            if (sameDayTasks.Any())\\r\\n            {\\r\\n                var totalHours = sameDayTasks.Sum(t => t.EstimatedHours ?? 1.0m) + (candidateTask.EstimatedHours ?? 1.0m);\\r\\n                \\r\\n                if (totalHours > 12) // 每日最�?2小时（含加班�?\\r\\n                {\\r\\n                    violations.Add($\\\"日工作负载超�? {candidateDate:yyyy-MM-dd}总工时{totalHours}小时超过12小时限制\\\");\\r\\n                }\\r\\n            }\\r\\n            \\r\\n            return violations;\\r\\n        }\\r\\n\\r\\n        /// <summary>\\r\\n        /// 检查人员不可用�?- 基于班次不可用性缓�?\\r\\n        /// </summary>\\r\\n        private List<string> CheckPersonnelUnavailability(\\r\\n            WorkOrderEntity candidateTask,\\r\\n            long personnelId,\\r\\n            GlobalAllocationContext context)\\r\\n        {\\r\\n            var violations = new List<string>();\\r\\n            \\r\\n            // 检查人员班次不可用�?\\r\\n            if (context.PersonnelUnavailabilityIndex.TryGetValue(personnelId, out var unavailabilityIndex))\\r\\n            {\\r\\n                var taskDate = candidateTask.WorkOrderDate.Date;\\r\\n                if (unavailabilityIndex.TryGetValue(taskDate, out var unavailableShifts))\\r\\n                {\\r\\n                    if (candidateTask.ShiftId.HasValue && unavailableShifts.Contains(candidateTask.ShiftId.Value))\\r\\n                    {\\r\\n                        violations.Add($\\\"人员不可�? {taskDate:yyyy-MM-dd}班次{candidateTask.ShiftId}人员不可�?);\\r\\n                    }\\r\\n                }\\r\\n            }\\r\\n            \\r\\n            return violations;\\r\\n        }\\r\\n\\r\\n        /// <summary>\\r\\n        /// 检查任务组合中的时间冲�?\\r\\n        /// 【深度实现】：多维度时间冲突检测，包括日期、班次、时间段重叠\\r\\n        /// </summary>\\r\\n        private bool HasTimeConflictInCombination(\\r\\n            List<WorkOrderEntity> taskCombination,\\r\\n            WorkOrderEntity newTask)\\r\\n        {\\r\\n            if (!taskCombination.Any()) return false;\\r\\n\\r\\n            foreach (var existingTask in taskCombination)\\r\\n            {\\r\\n                // 基础时间冲突：相同日�?班次\\r\\n                if (existingTask.WorkOrderDate.Date == newTask.WorkOrderDate.Date &&\\r\\n                    existingTask.ShiftId == newTask.ShiftId)\\r\\n                {\\r\\n                    return true;\\r\\n                }\\r\\n\\r\\n                // 扩展冲突检查：跨班次但在同一时间�?\\r\\n                if (IsTimeSlotOverlap(existingTask, newTask))\\r\\n                {\\r\\n                    return true;\\r\\n                }\\r\\n            }\\r\\n\\r\\n            return false;\\r\\n        }\\r\\n\\r\\n        /// <summary>\\r\\n        /// 检查时间段重叠\\r\\n        /// </summary>\\r\\n        private bool IsTimeSlotOverlap(WorkOrderEntity task1, WorkOrderEntity task2)\\r\\n        {\\r\\n            // 如果班次信息不完整，保守判断\\r\\n            if (task1.ShiftEntity == null || task2.ShiftEntity == null)\\r\\n                return false;\\r\\n\\r\\n            var start1 = task1.WorkOrderDate.Date.Add(task1.ShiftEntity.StartTime);\\r\\n            var end1 = task1.WorkOrderDate.Date.Add(task1.ShiftEntity.EndTime);\\r\\n            \\r\\n            var start2 = task2.WorkOrderDate.Date.Add(task2.ShiftEntity.StartTime);\\r\\n            var end2 = task2.WorkOrderDate.Date.Add(task2.ShiftEntity.EndTime);\\r\\n\\r\\n            // 处理跨日班次（如夜班22:00-06:00�?\\r\\n            if (task1.ShiftEntity.EndTime < task1.ShiftEntity.StartTime)\\r\\n            {\\r\\n                end1 = end1.AddDays(1);\\r\\n            }\\r\\n            if (task2.ShiftEntity.EndTime < task2.ShiftEntity.StartTime)\\r\\n            {\\r\\n                end2 = end2.AddDays(1);\\r\\n            }\\r\\n\\r\\n            // 检查时间段重叠\\r\\n            return start1 < end2 && start2 < end1;\\r\\n        }\\r\\n\\r\\n        /// <summary>\\r\\n        /// 构建人员任务矩阵\\r\\n        /// 【性能优化】：预计算人�?任务关联矩阵，加速冲突检�?\\r\\n        /// </summary>\\r\\n        private PersonnelTaskMatrix BuildPersonnelTaskMatrix(\\r\\n            Dictionary<(long TaskId, long PersonnelId), Variable> decisionVars,\\r\\n            GlobalAllocationContext context)\\r\\n        {\\r\\n            var matrix = new PersonnelTaskMatrix();\\r\\n\\r\\n            // 为每个人员构建可能的任务列表\\r\\n            foreach (var personnel in context.AvailablePersonnel)\\r\\n            {\\r\\n                var personnelTasks = context.Tasks\\r\\n                    .Where(task => decisionVars.ContainsKey((task.Id, personnel.Id)))\\r\\n                    .ToList();\\r\\n\\r\\n                matrix.PersonnelTaskMap[personnel.Id] = personnelTasks;\\r\\n            }\\r\\n\\r\\n            // 为每个任务构建可能的人员列表\\r\\n            foreach (var task in context.Tasks)\\r\\n            {\\r\\n                var taskPersonnel = context.AvailablePersonnel\\r\\n                    .Where(personnel => decisionVars.ContainsKey((task.Id, personnel.Id)))\\r\\n                    .ToList();\\r\\n\\r\\n                matrix.TaskPersonnelMap[task.Id] = taskPersonnel;\\r\\n            }\\r\\n\\r\\n            return matrix;\\r\\n        }\\r\\n\\r\\n        /// <summary>\\r\\n        /// 创建全局时间段约�?\\r\\n        /// 【架构创新】：跨人员的时间段约束，确保资源不冲�?\\r\\n        /// </summary>\\r\\n        private int CreateGlobalTimeSlotConstraints(\\r\\n            Solver solver,\\r\\n            Dictionary<(long TaskId, long PersonnelId), Variable> decisionVars,\\r\\n            GlobalAllocationContext context)\\r\\n        {\\r\\n            var constraintCount = 0;\\r\\n            \\r\\n            // 按时间段分组所有任�?\\r\\n            var timeSlotGroups = context.Tasks\\r\\n                .GroupBy(t => new TimeWindow \\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.3}}"}}
{"timestamp":"2025-09-22T13:28:58.961Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:29:00.597Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Continuing processing**"}}
{"timestamp":"2025-09-22T13:29:01.544Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":317078,"cached_input_tokens":285824,"output_tokens":2111,"reasoning_output_tokens":832,"total_tokens":319189},"last_token_usage":{"input_tokens":33657,"cached_input_tokens":31872,"output_tokens":77,"reasoning_output_tokens":0,"total_tokens":33734},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:29:01.544Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Continuing processing**"}],"content":null,"encrypted_content":"gAAAAABo0U8d5Vmpr5fboOLCiDFF68GPOFYOXrHplKtHXt5Ky_O1aaTK47FgBj4CHjIa7gv83gUk1R-lmSRZHYLQOvvJZPAJKiPgkRbFvqmgpF0P-nWsw9WKHAeXkRsDbCm54kMFUN3YJW3zyBUFFQYrVEZF6ilmgKgJ288XZBJOz3McexIv352Td17Ewk-4poWCOsun6bAGdtlRZwALHRlng393vo5BMzAxsoADrj2aQVTeoRVRN46wp_rDTe_mMlejJTJY-iGlYT_vxQMhCG-BjcQO8o10Y04TSML5TwvIglRzDsgZwymz2KCW3nSTEbu_SWivg6rLzlTsAU0EGfDtPiUOtfPME58ID_yRJOkDfYBbNXujhSiqQfjcfi6evXs6iDomgkf57j24Pdw1trIIhRm0BFgrWM_rDKCL918Os9fkmAoVh-RvgdClMjwjp0gfKMHS5r3iMj-mz8yAQVlkgaUQ4b7oFBD-fRtqtxMGzn5i8aTtUmHKKlqrIDZWNOQ8dej5kApjADxqH8iQ9cIiOhvwkjArj1cbU-dv2XUAtJgsu46Od20wPnFRY8gM69AZXx_ms8VOUwIkGw0QcU8W_t7Mqtyls_CSU8R5lWY2a8y6x8mv76C2jkzWo-Wb_QOZZOLkwe7Jb1MyypVEwYsWm1OVWv1zeGJSbIR_f-nET5A_RK-N7pMjEbGvvJvhzigyz6QS3SlxjoSBYTsCS9M1i9TdFsBVXIcKnte5cwWsy9mzdVdMu7AC5TVEuSByBSNY0BU5nCJ8VwG1tAlbhpidZx-SKXiBk2_yXqBpAAqEYsKYhZjzC87VFUgN1H6Jqh1J2lrbI2U0McnmaOSprABAcMYsX5lTQhLAEqIZpvmyYBgWWeex8GE="}}
{"timestamp":"2025-09-22T13:29:01.544Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"Get-Content \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\" | Select-Object -Skip 2060 -First 160\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_N5FnGfXWy2uKs6CqQxvhDtNG"}}
{"timestamp":"2025-09-22T13:29:01.544Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_N5FnGfXWy2uKs6CqQxvhDtNG","output":"{\"output\":\"                { \\r\\n                    Date = t.WorkOrderDate.Date,\\r\\n                    ShiftId = t.ShiftId ?? 0,\\r\\n                    StartTime = t.ShiftEntity?.StartTime ?? TimeSpan.Zero\\r\\n                })\\r\\n                .Where(g => g.Count() > 1) // 只处理有冲突可能的时间段\\r\\n                .ToList();\\r\\n\\r\\n            foreach (var timeGroup in timeSlotGroups)\\r\\n            {\\r\\n                var tasksInTimeSlot = timeGroup.ToList();\\r\\n                var timeWindow = timeGroup.Key;\\r\\n\\r\\n                // 为每个人员创建该时间段的约束\\r\\n                foreach (var personnel in context.AvailablePersonnel)\\r\\n                {\\r\\n                    var personnelVarsInTimeSlot = tasksInTimeSlot\\r\\n                        .Where(task => decisionVars.ContainsKey((task.Id, personnel.Id)))\\r\\n                        .Select(task => decisionVars[(task.Id, personnel.Id)])\\r\\n                        .ToList();\\r\\n\\r\\n                    if (personnelVarsInTimeSlot.Count > 1)\\r\\n                    {\\r\\n                        // 约束：同一人员在同一时间段最多执�?个任�?\\r\\n                        var constraint = solver.MakeConstraint(0, 1, \\r\\n                            $\\\"global_timeslot_{personnel.Id}_{timeWindow.Date:yyyyMMdd}_{timeWindow.ShiftId}\\\");\\r\\n                        \\r\\n                        foreach (var variable in personnelVarsInTimeSlot)\\r\\n                        {\\r\\n                            constraint.SetCoefficient(variable, 1);\\r\\n                        }\\r\\n                        constraintCount++;\\r\\n                    }\\r\\n                }\\r\\n            }\\r\\n\\r\\n            return constraintCount;\\r\\n        }\\r\\n\\r\\n        /// <summary>\\r\\n        /// 创建批次完整性约�?\\r\\n        /// 【业务逻辑】：确保批次内任务分配的一致性和完整�?\\r\\n        /// </summary>\\r\\n        private int CreateBatchIntegrityConstraints(\\r\\n            Solver solver,\\r\\n            Dictionary<(long TaskId, long PersonnelId), Variable> decisionVars,\\r\\n            Dictionary<string, Variable> auxiliaryVars,\\r\\n            GlobalAllocationContext context)\\r\\n        {\\r\\n            var constraintCount = 0;\\r\\n\\r\\n            // 1. 项目连续性约束增�?\\r\\n            var projectGroups = context.Tasks\\r\\n                .GroupBy(t => ExtractProjectFromWorkOrderCode(t.WorkOrderCode))\\r\\n                .Where(g => g.Count() > 1)\\r\\n                .ToList();\\r\\n\\r\\n            foreach (var projectGroup in projectGroups)\\r\\n            {\\r\\n                var projectTasks = projectGroup.ToList();\\r\\n                var projectCode = projectGroup.Key;\\r\\n\\r\\n                // 创建项目一致性指示变�?\\r\\n                foreach (var personnel in context.AvailablePersonnel)\\r\\n                {\\r\\n                    var projectParticipationVars = projectTasks\\r\\n                        .Where(task => decisionVars.ContainsKey((task.Id, personnel.Id)))\\r\\n                        .Select(task => decisionVars[(task.Id, personnel.Id)])\\r\\n                        .ToList();\\r\\n\\r\\n                    if (projectParticipationVars.Count > 1)\\r\\n                    {\\r\\n                        var participationVar = solver.MakeBoolVar(\\r\\n                            $\\\"project_participation_{projectCode}_{personnel.Id}\\\");\\r\\n\\r\\n                        // 如果参与项目，则至少分配一个任�?\\r\\n                        var constraint = solver.MakeConstraint(0, double.PositiveInfinity,\\r\\n                            $\\\"project_integrity_{projectCode}_{personnel.Id}\\\");\\r\\n                        \\r\\n                        constraint.SetCoefficient(participationVar, -1);\\r\\n                        foreach (var taskVar in projectParticipationVars)\\r\\n                        {\\r\\n                            constraint.SetCoefficient(taskVar, 1);\\r\\n                        }\\r\\n                        constraintCount++;\\r\\n\\r\\n                        // 限制项目参与人员数量\\r\\n                        auxiliaryVars[$\\\"project_participation_{projectCode}_{personnel.Id}\\\"] = participationVar;\\r\\n                    }\\r\\n                }\\r\\n            }\\r\\n\\r\\n            // 2. 工作负载平衡约束\\r\\n            var totalTasks = context.Tasks.Count;\\r\\n            var totalPersonnel = context.AvailablePersonnel.Count;\\r\\n            var avgWorkload = (double)totalTasks / totalPersonnel;\\r\\n            var maxDeviation = Math.Ceiling(avgWorkload * 0.3); // 允许30%偏差\\r\\n\\r\\n            foreach (var personnel in context.AvailablePersonnel)\\r\\n            {\\r\\n                var personnelTasks = decisionVars\\r\\n                    .Where(kvp => kvp.Key.PersonnelId == personnel.Id)\\r\\n                    .Select(kvp => kvp.Value)\\r\\n                    .ToList();\\r\\n\\r\\n                if (personnelTasks.Any())\\r\\n                {\\r\\n                    // 工作负载不应过度偏离平均�?\\r\\n                    var constraint = solver.MakeConstraint(\\r\\n                        Math.Max(0, avgWorkload - maxDeviation),\\r\\n                        avgWorkload + maxDeviation,\\r\\n                        $\\\"workload_balance_{personnel.Id}\\\");\\r\\n\\r\\n                    foreach (var taskVar in personnelTasks)\\r\\n                    {\\r\\n                        constraint.SetCoefficient(taskVar, 1);\\r\\n                    }\\r\\n                    constraintCount++;\\r\\n                }\\r\\n            }\\r\\n\\r\\n            return constraintCount;\\r\\n        }\\r\\n\\r\\n        /// <summary>\\r\\n        /// 【Ultra think核心】添加人员班次不可用性硬约束\\r\\n        /// 【业务逻辑】：确保线性规划模型不会将任务分配给在该时间段不可用的人员\\r\\n        /// 【约束策略】：硬约�?- 直接禁止不可用分配，不允许任何违�?\\r\\n        /// 【数据来源】：DateShiftUnavailablePersonnel缓存 + PersonnelUnavailabilityIndex索引\\r\\n        /// 【性能优化】：仅对已创建决策变量的组合进行约束，避免无效约�?\\r\\n        /// </summary>\\r\\n        private async Task<int> AddPersonnelUnavailabilityConstraints(\\r\\n            Solver solver,\\r\\n            Dictionary<(long TaskId, long PersonnelId), Variable> decisionVars,\\r\\n            GlobalAllocationContext context)\\r\\n        {\\r\\n            var constraintCount = 0;\\r\\n            \\r\\n            try\\r\\n            {\\r\\n                _logger.LogDebug(\\\"🚫 开始构建人员班次不可用性硬约束\\\");\\r\\n                \\r\\n                var startTime = DateTime.Now;\\r\\n                var processedVariables = 0;\\r\\n                var constrainedVariables = 0;\\r\\n\\r\\n                // 【Ultra think策略】：对所有决策变量检查不可用性约�?\\r\\n                foreach (var kvp in decisionVars)\\r\\n                {\\r\\n                    var (taskId, personnelId) = kvp.Key;\\r\\n                    var variable = kvp.Value;\\r\\n                    processedVariables++;\\r\\n\\r\\n                    // 查找对应的任务实�?\\r\\n                    var task = context.Tasks.FirstOrDefault(t => t.Id == taskId);\\r\\n                    if (task == null) continue;\\r\\n\\r\\n                    // 【核心检查】：使用多重策略检查人员不可用�?\\r\\n                    var isUnavailable = await IsPersonnelUnavailableForTaskAsync(task, personnelId, context);\\r\\n                    \\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.3}}"}}
{"timestamp":"2025-09-22T13:29:01.544Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:29:03.313Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Continuing exploration**"}}
{"timestamp":"2025-09-22T13:29:04.160Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":352472,"cached_input_tokens":319488,"output_tokens":2188,"reasoning_output_tokens":832,"total_tokens":354660},"last_token_usage":{"input_tokens":35394,"cached_input_tokens":33664,"output_tokens":77,"reasoning_output_tokens":0,"total_tokens":35471},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:29:04.160Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Continuing exploration**"}],"content":null,"encrypted_content":"gAAAAABo0U8gGLZZiN3G1Lg_gd-zDwSWN2Qn0Oj9NMphc9_hnwNv3PqYjiepui9rZ62x4BlxeLJjy7JwPfZos7c37TfwsiXWSGmdtv5yczQvGRqY-VrXwioRarwO_o0CoPD9ivycQT5V_1pv7fGpyt2yrLfjbJV4BpM6Buwyty4-7zJSOi_9LW_0At3zE4sGROksO-ap4SetU3qV-TKYSuKNLZj-DBEEdBhjEa_ct_f-tuQqhEVatfNqDZbe_IcU76kL0_T0hNYX_G7DTUwy8aqB2iBncut5fQEqifgt7o6d7MSdimDFr41NcPSkX2tU_WYZ0FV2dtRU3HDXeAgNPyqj7RSCnBjgmmwCou9dKBWOSB4-GEpwNBzGvYTT6xmtk96Dmc5LRZhdwmd48HZp8bwQ85uE2gp4v3yQSkWul4hw5FqWs-rUNSeLxW9jiBfJaG-JX8WY4lZmZtv0LzoMV5wCa8fZLDXpK9Z9RJF1DQjTOI3dzSqSyrDjJgUzZeA7OFMqZbJDwi-L35vJ9FJQTZu3xxl5jjU1mInc1tBmrQ9u6fFSWwTwSzk28C0mra36Ji6dNWF_g3aX0imvlM83oaJlHHgqAITe07wG9n18J3ckytPYvzwNcRj6mZDm04ut2Mi5PxsD_WONCpKVgZXHkQwRl1I_kFNuKQQCUXgG9Crf-hFkbTFmWjtO6am83VxsHtZ9nvlwSrubTa_uG8-TOwvDci1LjuVZWX6t2NnZ4HORcYjUhPCayLQJEyfGhH_mso4lyCmxVPsO1hi5JCZuD9unDTlYG9weH13M8zF3YUNzqbOfG55N2CJO3M72FtiMZTNC4xVcpJq3kxbA7pnp2fUHYBeXWNcRCKbzD_-eN3m3-QO4cK8J8OE="}}
{"timestamp":"2025-09-22T13:29:04.160Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"Get-Content \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\" | Select-Object -Skip 2220 -First 160\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_m4iLu4fonxoUaunXzHa7wkRb"}}
{"timestamp":"2025-09-22T13:29:04.160Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_m4iLu4fonxoUaunXzHa7wkRb","output":"{\"output\":\"                    if (isUnavailable)\\r\\n                    {\\r\\n                        // 【硬约束】：强制该决策变量为0 (不允许分�?\\r\\n                        var constraint = solver.MakeConstraint(0, 0, $\\\"unavailable_{taskId}_{personnelId}\\\");\\r\\n                        constraint.SetCoefficient(variable, 1);\\r\\n                        constraintCount++;\\r\\n                        constrainedVariables++;\\r\\n                        \\r\\n                        _logger.LogTrace(\\\"🚫 应用不可用性约�?- 任务{TaskId}人员{PersonnelId}在{Date}班次{ShiftId}不可�?, \\r\\n                            taskId, personnelId, task.WorkOrderDate.ToString(\\\"yyyy-MM-dd\\\"), task.ShiftId);\\r\\n                    }\\r\\n                }\\r\\n\\r\\n                var elapsedMs = (DateTime.Now - startTime).TotalMilliseconds;\\r\\n                \\r\\n                _logger.LogInformation(\\\"�?人员班次不可用性约束构建完�?- 耗时：{ElapsedMs}ms，处理变量：{ProcessedCount}，约束变量：{ConstrainedCount}，约束数量：{ConstraintCount}，约束率：{ConstraintRate:P2}\\\",\\r\\n                    elapsedMs, processedVariables, constrainedVariables, constraintCount, \\r\\n                    processedVariables > 0 ? (double)constrainedVariables / processedVariables : 0);\\r\\n\\r\\n                await Task.CompletedTask;\\r\\n                return constraintCount;\\r\\n            }\\r\\n            catch (Exception ex)\\r\\n            {\\r\\n                _logger.LogError(ex, \\\"💥 人员班次不可用性约束构建异�?);\\r\\n                throw;\\r\\n            }\\r\\n        }\\r\\n\\r\\n        #endregion\\r\\n\\r\\n        #region 人员不可用性检查辅助方�?\\r\\n\\r\\n        /// <summary>\\r\\n        /// 【Ultra think方法】检查人员在指定任务时间是否不可用（同步版本�?\\r\\n        /// 【高性能设计】：优先使用缓存索引，提供快速决策能�?\\r\\n        /// 【多重验证】：DateShiftUnavailablePersonnel + PersonnelUnavailabilityIndex双重验证\\r\\n        /// </summary>\\r\\n        private bool IsPersonnelUnavailableForTask(WorkOrderEntity task, long personnelId, GlobalAllocationContext context)\\r\\n        {\\r\\n            try\\r\\n            {\\r\\n                // 【验证策�?】使用DateShiftUnavailablePersonnel快速检�?\\r\\n                var dateShiftKey = $\\\"{task.WorkOrderDate:yyyy-MM-dd}_{task.ShiftId}\\\";\\r\\n                if (context.DateShiftUnavailablePersonnel.TryGetValue(dateShiftKey, out var unavailablePersonnel))\\r\\n                {\\r\\n                    if (unavailablePersonnel.Contains(personnelId))\\r\\n                    {\\r\\n                        return true; // 该人员在此日期班次不可用\\r\\n                    }\\r\\n                }\\r\\n\\r\\n                // 【验证策�?】使用PersonnelUnavailabilityIndex进行人员维度检�?\\r\\n                if (context.PersonnelUnavailabilityIndex.TryGetValue(personnelId, out var unavailabilityIndex))\\r\\n                {\\r\\n                    var taskDate = task.WorkOrderDate.Date;\\r\\n                    if (unavailabilityIndex.TryGetValue(taskDate, out var unavailableShifts))\\r\\n                    {\\r\\n                        if (task.ShiftId.HasValue && unavailableShifts.Contains(task.ShiftId.Value))\\r\\n                        {\\r\\n                            return true; // 人员在该日期的该班次不可�?\\r\\n                        }\\r\\n                    }\\r\\n                }\\r\\n                \\r\\n                // 检查历史任务人员的分配\\r\\n                if (context.PersonnelHistoryTasks.TryGetValue(personnelId, out var historyTask))\\r\\n                {\\r\\n                    var taskDate = task.WorkOrderDate.Date;\\r\\n\\r\\n                    if (historyTask.Any(m => m.WorkDate.Date == taskDate))\\r\\n                    {\\r\\n                        return true;\\r\\n                    }\\r\\n                }\\r\\n                \\r\\n                return false; // 人员可用\\r\\n            }\\r\\n            catch (Exception ex)\\r\\n            {\\r\\n                _logger.LogWarning(ex, \\\"⚠️ 检查人员不可用性异�?- 任务{TaskId}人员{PersonnelId}，默认为不可�?, \\r\\n                    task.Id, personnelId);\\r\\n                return true; // 异常情况下保守处理，标记为不可用\\r\\n            }\\r\\n        }\\r\\n\\r\\n        /// <summary>\\r\\n        /// 【Ultra think方法】检查人员在指定任务时间是否不可用（异步版本�?\\r\\n        /// 【扩展支持】：为未来集成更复杂的不可用性检查逻辑预留接口\\r\\n        /// </summary>\\r\\n        private async Task<bool> IsPersonnelUnavailableForTaskAsync(WorkOrderEntity task, long personnelId, GlobalAllocationContext context)\\r\\n        {\\r\\n            // 目前直接调用同步版本，保持异步接口以便未来扩�?\\r\\n            await Task.CompletedTask;\\r\\n            return IsPersonnelUnavailableForTask(task, personnelId, context);\\r\\n        }\\r\\n\\r\\n        #endregion\\r\\n    }\\r\\n\\r\\n    /// <summary>\\r\\n    /// 人员任务矩阵 - 支持高效的关联查�?\\r\\n    /// </summary>\\r\\n    public class PersonnelTaskMatrix\\r\\n    {\\r\\n        public Dictionary<long, List<WorkOrderEntity>> PersonnelTaskMap { get; set; } = new();\\r\\n        public Dictionary<long, List<GlobalPersonnelInfo>> TaskPersonnelMap { get; set; } = new();\\r\\n    }\\r\\n\\r\\n    /// <summary>\\r\\n    /// 时间窗口定义\\r\\n    /// </summary>\\r\\n    public class TimeWindow : IEquatable<TimeWindow>\\r\\n    {\\r\\n        public DateTime Date { get; set; }\\r\\n        public long ShiftId { get; set; }\\r\\n        public TimeSpan StartTime { get; set; }\\r\\n\\r\\n        public bool Equals(TimeWindow other)\\r\\n        {\\r\\n            if (other == null) return false;\\r\\n            return Date.Date == other.Date.Date && \\r\\n                   ShiftId == other.ShiftId && \\r\\n                   StartTime == other.StartTime;\\r\\n        }\\r\\n\\r\\n        public override bool Equals(object obj) => Equals(obj as TimeWindow);\\r\\n        \\r\\n        public override int GetHashCode() => HashCode.Combine(Date.Date, ShiftId, StartTime);\\r\\n    }\\r\\n\\r\\n    /// <summary>\\r\\n    /// 冲突严重程度枚举\\r\\n    /// </summary>\\r\\n    public enum ConflictSeverity\\r\\n    {\\r\\n        None = 0,        // 无冲�?\\r\\n        Low = 1,         // 轻微冲突\\r\\n        Medium = 2,      // 中等冲突\\r\\n        High = 3,        // 严重冲突\\r\\n        Critical = 4     // 关键冲突\\r\\n    }\\r\\n\\r\\n    /// <summary>\\r\\n    /// WorkOrderEntity扩展方法 - 为LinearProgrammingEngine提供辅助功能\\r\\n    /// </summary>\\r\\n    public static class WorkOrderEntityExtensions\\r\\n    {\\r\\n        /// <summary>\\r\\n        /// 【深度实现】为验证目的克隆WorkOrderEntity\\r\\n        /// 【业务思考】：在线性规划验证过程中，需要模拟分配的临时任务对象\\r\\n        /// 【技术要点】：仅复制验证所需的关键字段，避免整体对象克隆的性能开销\\r\\n        /// </summary>\\r\\n        public static WorkOrderEntity CloneForValidation(this WorkOrderEntity original)\\r\\n        {\\r\\n            return new WorkOrderEntity\\r\\n            {\\r\\n                Id = original.Id,\\r\\n                ProjectNumber = original.ProjectNumber,\\r\\n                ProjectCategory = original.ProjectCategory,\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.3}}"}}
{"timestamp":"2025-09-22T13:29:04.160Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:29:19.415Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Summarizing engine architecture and implementation status**\n\nI'm gathering key points about the engine's structure and functionality, focusing on the actual implemented features versus planned ones. There are many core functions and constraint sets that are currently commented out or stubbed, including dynamic shift rules and certain fairness rewards. The engine uses Google OR-Tools with CBC MIP, orchestrated mainly through `OptimizeAsync`, which builds variables, applies constraints, solves, and processes results, though some processing steps may be missing or inactive. I'll also look closer at how the solve step and post-solve processing are handled to clarify the flow."}}
{"timestamp":"2025-09-22T13:29:19.927Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":389722,"cached_input_tokens":354816,"output_tokens":2776,"reasoning_output_tokens":1344,"total_tokens":392498},"last_token_usage":{"input_tokens":37250,"cached_input_tokens":35328,"output_tokens":588,"reasoning_output_tokens":512,"total_tokens":37838},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:29:19.927Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Summarizing engine architecture and implementation status**\n\nI'm gathering key points about the engine's structure and functionality, focusing on the actual implemented features versus planned ones. There are many core functions and constraint sets that are currently commented out or stubbed, including dynamic shift rules and certain fairness rewards. The engine uses Google OR-Tools with CBC MIP, orchestrated mainly through `OptimizeAsync`, which builds variables, applies constraints, solves, and processes results, though some processing steps may be missing or inactive. I'll also look closer at how the solve step and post-solve processing are handled to clarify the flow."}],"content":null,"encrypted_content":"[encoded data, 4876 characters]"}}
{"timestamp":"2025-09-22T13:29:19.927Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"Get-Content \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\" | Select-Object -Skip 60 -First 120\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_rweOwGyO8NadOZLvEg03mwYu"}}
{"timestamp":"2025-09-22T13:29:19.927Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_rweOwGyO8NadOZLvEg03mwYu","output":"{\"output\":\"                using var solver = CreateAdvancedSolver();\\r\\n\\r\\n                // 第二步：构建决策变量矩阵 (x[i,j] = 1表示任务i分配给人员j)\\r\\n                var decisionVariables = BuildDecisionVariables(solver, context);\\r\\n                _logger.LogDebug(\\\"📊 决策变量构建完成 - 变量数量：{VariableCount}\\\", decisionVariables.Count);\\r\\n\\r\\n                // 第三步：构建辅助变量 (支持复杂约束建模)\\r\\n                var auxiliaryVariables = BuildAuxiliaryVariables(solver, context, decisionVariables);\\r\\n                _logger.LogDebug(\\\"🔧 辅助变量构建完成 - 辅助变量数量：{AuxCount}\\\", auxiliaryVariables.Count);\\r\\n\\r\\n                // 第四步：Level 1 基础约束 - 对应遗传算法的基础约束验证\\r\\n                await AddLevel1BasicConstraints(solver, decisionVariables, auxiliaryVariables, context);\\r\\n\\r\\n                // 第五步：Level 2 组合约束 - 对应遗传算法的组合约束验�? \\r\\n                await AddLevel2CombinationConstraints(solver, decisionVariables, auxiliaryVariables, context);\\r\\n\\r\\n                // 第六步：Level 3 业务约束 - 对应遗传算法的业务逻辑约束\\r\\n                await AddLevel3BusinessConstraints(solver, decisionVariables, auxiliaryVariables, context);\\r\\n\\r\\n                // 第七步：公平性约�?- 对应遗传算法的负载均衡机�?\\r\\n                AddFairnessConstraints(solver, decisionVariables, auxiliaryVariables, context);\\r\\n\\r\\n                // 第八步：设置多维度目标函�?- 对应遗传算法的适应度函�?\\r\\n                SetEnhancedObjectiveFunction(solver, decisionVariables, auxiliaryVariables, context);\\r\\n\\r\\n                // 第九步：执行求解\\r\\n                _logger.LogInformation(\\\"🔍 开始求解增强版线性规划模�?..\\\");\\r\\n                var resultStatus = solver.Solve();\\r\\n                \\r\\n                stopwatch.Stop();\\r\\n                \\r\\n                // 第十步：解析和验证结�?\\r\\n                var solution = await ProcessEnhancedSolverResult(solver, decisionVariables, auxiliaryVariables, \\r\\n                    context, resultStatus, stopwatch.ElapsedMilliseconds);\\r\\n                \\r\\n                return solution;\\r\\n            }\\r\\n            catch (Exception ex)\\r\\n            {\\r\\n                stopwatch.Stop();\\r\\n                _logger.LogError(ex, \\\"💥 增强版线性规划优化异常，耗时：{ElapsedMs}ms\\\", stopwatch.ElapsedMilliseconds);\\r\\n                \\r\\n                return CreateFailureSolution(ex.Message, stopwatch.ElapsedMilliseconds);\\r\\n            }\\r\\n        }\\r\\n\\r\\n        #region 求解器和变量构建\\r\\n\\r\\n        /// <summary>\\r\\n        /// 创建高性能求解�?- 支持大规模约束优�?\\r\\n        /// </summary>\\r\\n        private Solver CreateAdvancedSolver()\\r\\n        {\\r\\n            var solver = Solver.CreateSolver(SOLVER_TYPE);\\r\\n            if (solver == null)\\r\\n            {\\r\\n                throw new InvalidOperationException(\\\"无法创建增强版线性规划求解器\\\");\\r\\n            }\\r\\n\\r\\n            // 高性能配置\\r\\n            solver.SetTimeLimit(MAX_SOLVER_TIME_SECONDS * 1000);\\r\\n            \\r\\n            // 设置优化参数\\r\\n            solver.SetSolverSpecificParametersAsString(\\r\\n                \\\"cuts=1 \\\" +           // 启用割平�?\\r\\n                \\\"heuristics=1 \\\" +     // 启用启发式算�?\\r\\n                \\\"presolve=1 \\\" +       // 启用预处�?\\r\\n                \\\"threads=0\\\"           // 使用所有可用线�?\\r\\n            );\\r\\n\\r\\n            _logger.LogInformation(\\\"🔧 高性能求解器创建完成，配置：时间限制{TimeLimit}s，多线程支持\\\", MAX_SOLVER_TIME_SECONDS);\\r\\n            return solver;\\r\\n        }\\r\\n\\r\\n        /// <summary>\\r\\n        /// 【Ultra think增强】构建决策变�?- 集成人员班次不可用性的智能变量生成\\r\\n        /// 【核心优化】：在变量创建阶段就排除不可用组合，大幅提升求解效率\\r\\n        /// 【三层优化】：预筛选结�?+ 不可用性检�?+ 评分阈值，实现精确的变量裁�?\\r\\n        /// 【性能提升】：预计减少20-40%的决策变量数量，显著提升求解速度\\r\\n        /// </summary>\\r\\n        private Dictionary<(long TaskId, long PersonnelId), Variable> BuildDecisionVariables(\\r\\n            Solver solver, GlobalAllocationContext context)\\r\\n        {\\r\\n            var variables = new Dictionary<(long TaskId, long PersonnelId), Variable>();\\r\\n            var createdCount = 0;\\r\\n            var skippedCount = 0;\\r\\n            var unavailabilitySkippedCount = 0;\\r\\n            \\r\\n            foreach (var task in context.Tasks)\\r\\n            {\\r\\n                foreach (var personnel in context.AvailablePersonnel)\\r\\n                {\\r\\n                    var prefilterKey = $\\\"{task.Id}_{personnel.Id}\\\";\\r\\n                    \\r\\n                    // 【Ultra think优化1】首先检查人员班次不可用�?- 硬排�?\\r\\n                    if (IsPersonnelUnavailableForTask(task, personnel.Id, context))\\r\\n                    {\\r\\n                        unavailabilitySkippedCount++;\\r\\n                        skippedCount++;\\r\\n                        _logger.LogDebug(\\\"🚫 跳过不可用组�?- 任务{TaskId}人员{PersonnelId}在{Date}班次{ShiftId}不可�?, \\r\\n                            task.Id, personnel.Id, task.WorkOrderDate.ToString(\\\"yyyy-MM-dd\\\"), task.ShiftId);\\r\\n                        continue;\\r\\n                    }\\r\\n                    \\r\\n                    // 【Ultra think优化2】基于预筛选结果的智能决策\\r\\n                    if (context.PrefilterResults.TryGetValue(prefilterKey, out var prefilterResult))\\r\\n                    {\\r\\n                        // 对于评分较高的分配，即使标记为不可行也创建变量（可能是保守评估）\\r\\n                        if (prefilterResult.IsFeasible || prefilterResult.PrefilterScore > 30.0)\\r\\n                        {\\r\\n                            var variableName = $\\\"x_{task.Id}_{personnel.Id}\\\";\\r\\n                            var variable = solver.MakeBoolVar(variableName);\\r\\n                            variables[(task.Id, personnel.Id)] = variable;\\r\\n                            createdCount++;\\r\\n                        }\\r\\n                        else\\r\\n                        {\\r\\n                            skippedCount++;\\r\\n                        }\\r\\n                    }\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.3}}"}}
{"timestamp":"2025-09-22T13:29:19.927Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:29:31.016Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Preparing detailed engine summary and gathering code line numbers**"}}
{"timestamp":"2025-09-22T13:29:31.549Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":429151,"cached_input_tokens":392576,"output_tokens":3293,"reasoning_output_tokens":1792,"total_tokens":432444},"last_token_usage":{"input_tokens":39429,"cached_input_tokens":37760,"output_tokens":517,"reasoning_output_tokens":448,"total_tokens":39946},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:29:31.549Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Preparing detailed engine summary and gathering code line numbers**"}],"content":null,"encrypted_content":"gAAAAABo0U88Cq912HQfXCk0_8mIYwo9zLm1Irj7rV0rfczfYmmoZI4ht_wkPS5oe-dqD09tHmN0hNnmyh_t0Tt5BA3mqhS95pCEfCSYSaLK-qzaZxyFoBzSGSGdBL7sQM7FUEJE5Zdj8WXSpYgulzHz7DIgNmRNGpQO7jWnT-hO7qXgwpKmno5c-jldbyTFFbWHIhMYMv4oPQWyCH72kLVtRt0KhLhfrjXH4WhP5ZVfPtm85pUzIKL3r3te2d80qG-dTXqOVNm_TtlNLUOFcIRVOP22mTNdT_F7DT_lBwzBE0UfOFHTO9HNnQOPb-AChqsVYHPfvmjo9pxDRRUZ46H16mfw6ECjQ2M7jdKkiDI5Dv-xMj0rhWsb9KTUs6fjuZKKjRIs1ozS20p_F0haujKykmNRQOW9BHJgr1TpnjLSKUeqzS8-8FehwaTjRtSAUZ-IY0itUoaGN6lai2y_4LdL95-6brpRhz1C-wdb5Dtvwdtv__EzDwE4c9iivPL_Ad00SPk8nctN39ebirVhs5VWoeY2VCnZ0mUoWKPbqra-VAw4W9QN8L1MXrbn7JrPTslA7wwZaUz5mXNv3ZhnQKw2IRr9DEuS3PgSOi1DN1V2nTgwLVgG6Ocv10JEcmYW1uWUDHv7glffcwVdoQpqb1ISu7ThlNLxIOeMfB1wjC-TAXh0v11DJJ_s2b0SKutFGDDwPxwlnFZBgINZ7-jyDM_nUyUXZn3xyGTKTajWMlsE71_Re2q5dQfEFMzuZekBYHzCI4Zoe30UBWE7Wyeh00e3PLHNOgQIf4fPAEQxdnSOpLYSbVuRIzTRNrozMcUTzS-dGqZb09CoRtVVlnN1mUTWcWMk-PCkcc71M-Yy0V0U_nYZf8WImRw4Jhvvt7DnZn17hMrcSz9xw9UGTwOB1LiFsFChSapSzlHhVxMWWucCliPgYqRHjAmwcsPK5aYP3kvVmV8Ajbzxdkob-QYq1V7T6RywrcgRNEBOHt9z-vS6uuhd55aHPon4QGruh33uYCWRkZcHxpe959k4Cdxzk8QoFYHP1rLfpybBPw1XPYF8brVwpdWdJNT9C2qQlZ_aOOajbbtPlplSs1pm2I3pPCckCzwxIJtWR2Xx2qSR0Fj6TTP6-jSHUGfNDq7ux_JzCph404UbMKJM3zhE9NI7KL3UDj9b2AnSlnOTZwUhjM4BvPj1n02WdWGuRo8X7YTmu_iiqgMxfOK40zgy8idBk6PMITxXJQWTSWyuvRGaRksD_9KEBIB777Bkg-F51p_0umae-7e-OEDJXfXX6qmnk_yOzoOEX4y69JBM67Zv0I5G7xbHf47wIRajdM9xcM-FY6CXLRV_-uzv2LPW3Iwb9N5z_glGzZLRHQ8tD6scZiNmIVFoYmyiJQ1wjsV6cg2pNwMJyji3Ss4cB3rbPpnBgxwJMClv6FrtKYPdcobR8rmqp4lPr5uSKJ6sYcmkoYGjrCfZ9z44RGUjYthliihM7QT7qMYOd00MAPNY-ajUEt2bLv0fAXvZymGP2tS8cw-rc5uM7vylHPoUeWTMVCbUA5adUejmnsCXlWLfv4WaagClUy8QJDwDwB0ZEhjdMM2bj3eXIUSnNCc5Sp3dBIeHb5mGA0V5_7WuKiXg038FIE-a4i_GRthwxI0vv6Ob5TMZMaF72ctoDaHHtsBb0kvUmJiE5MAEQSqKVzCzxtmvsZkPbyEqBH6XxU6EV594mZucY82DJuD2mDlMQrO6lu8ewi8l59yL4TbdHZ6Z68b5goG0cowDRDSdN2az7ubR1OBgLgwFZMsz1ELnpTnVzmSNu-c75ryWyohd0fb3NVchPjUzBn84NYwFeoJtWf-n_fBWcqVx4PwYYjOhibvT7p49yKTyRTmzG5gb9Jf-eLB6_00Vjs5Tcn4EBm7PvKMs9mjW8aASyulcxpW4HdhogbrbI6ttkeiIUlJFF5dNKaZGeWh3SxteaCjwWjIBCYZY29v844WEfOoHrClhgFORxhL1yWaFaziMjOTBeuXwGXIbLNDcwu-3N2d5UPlDrst8zuJAGtHNbpzrtxHzK0-ZprX3VS-ly6c2uoMoCXtRRABFAus73PTU6T06BCNC-26o5O4pdwDfpf3B87VtTR7HxRTaNtgBK_gf42uLqpEHraMx_Nlr09e6gQwG5_oroUZBuKRsTVxSmu2_jT_NkY-9aRbEe3wgbEuv8ydhJJpVpZw6-4lYdKSdHiIt1x-BduM_i83fwy2s7y7cuB47noDVYWmY5TdaX3DRYUQKpZlp6dxI0xSPGSAZNMyiJcA7Kx0aDkUgkAIGPGkgmm6erR--lwRY6OhszwxivG3qFGaMUrdO-a-p_8MgaW3W38U1lmUbMIARq4zppR9BHSHf_S8THVniAuReBHvbHPpQ3gHbKZ5S0pNVJa0kMuaVvkYOYkqloPHCzSN5COP-lOmuPt2lrLEnKwBkGOiu6FvFboOSX19menm8OrqZbfIgUc3eC47jwMnc2tSFEsujG4ogF2R6fOI8jHqL8nB1PixBUg_RbN_oY66mh0fOyPuGMGB0Zek8S4aV4R4ILQKpEKxi6uiZJBTZH0UD85VNMSWiOWIQ2MK_linZzgn6kW0mjWgsaPWORGfbiI4ecQyRpilrCox_ZaeQ1hRK1M-SWEvMwcMmkjJiEDZcb9qCci2ZuT3F6K4OZ3ljR3XMJZBcE2RAtsnXtjSH3gCh-1kK9-ZQpttAhe3dJuM6ZHv18rQ9p4vM3HyqEpRwb3GbyQrIfFXw5Aml1lMv9mAqtBEgCv4GR961SvekvHgh3_EO2rR9Oq1Rj_VTzNpsQHvnBZCkCx5i4vvNzLUjQq-dH9zbTxGwj6uGtEHwfanIyrbnitUCPm30Nm_1-SmL18IXJf2K17GAoR041yupOaRXGunwiZI_Hy7KtMqtJJW-OZS-W8HcBiq4b7Fi6_krPZgJ8Brsh8b8cR_xjS3jrpyEtxmqGMu1jfnMGpY73J2160MpChyd5O6hrUHNGxLfjasGPxxgLC3f_6cPL_9jiIlo6w3S4nOtJgRvrdGG4MKYJpq8wGfGz1ugdn3ON7qKI5jgrkZBLnOhRaHWUerA6Exn0rWHmoC1wCQuIplyiLI_p8k0prlXs8p-xcsR96Z0oX-7OsGDbswjPpAG7aTC6_sftwlaBNPhcdIX5jiyF0mygnU8PhUhHERiQob80f8EUmWH4OIhYq1K70neZIJw9F_qSd9gfiigRZh_CfFOkvJ6u-B8VyFmU_TTAIEmjsq64dRkyAP6siLtKYU6YqNtxlSSZBnxwnVoR2p1NoaHA8JgPWksXKWjSg-w0gLkPO7A_fZr9WC7uLCprLBS3Cu8lxbYHL9xiwSJnFLmDm_MSUH5eZd7obxfnnLE_ZYiURfRPLrlS4XsV1iCrfbF8Hn2VIrCF3Hrw2KYDzOz8jN-L6m8mqdQT-A3cBHVLPkPOeK-davvmEsqB55c2VrWbldSVEwICUvQDyMYqbjjY1X0L0pVzIqZXSrsFK47GdOriGff272tNMczz2phh_YV00pCR55GVbS7VnyoBbuu1W_72dgmZoeSNJYlpEWvUlM8JMWi_H8_zOyWO8svOItqZvHUPD3KiRheFHQxdv_6M5xF1l3pZ8EbwiQN7kuP9lXgwSxyeK8QuQGFlkEtQj1bOgMqiqmGBCD9lKH_TC_3IX3RPwASj5xJc4RtMesVqvMvQBcbaEEl0ZnJD5g13ez1W-plMWTbgvFV3kqkNc9HdLVI9bJSDOTkdm5gAq84EUSi-fMVN_Srl27FhDZTmQHqODTyXF_T1ypBO2CFUhZdpsQGGRrwZmyl1ZxywsK63ltPv2XgK2v8uz-FKnBC_2jTF1_cIIxJNIbVKOxkH2Xtje8m5BIWI43KRE7qPQRWG3qACf9B2cygC9-xHCeGWCzMqVWcM_cvuIEEQQfy4t6fUMEj3BKv5SHMXLwG5ZkcDea0HFd-zxj2B8_x4uOBXv1er8kxfnoi2Dfd9fVxsDpdtLad9jN_1rLjSWepKQ_AGlG1YIY9y0UxQfPg40WXwftt8ZKtl7dBh-d5YolO7Q=="}}
{"timestamp":"2025-09-22T13:29:31.549Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"rg --line-number \\\"OptimizeAsync\\\" \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\"\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_x04Qw97jHkaP11DuIASBx7Cu"}}
{"timestamp":"2025-09-22T13:29:31.549Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_x04Qw97jHkaP11DuIASBx7Cu","output":"{\"output\":\"51:        public async Task<GlobalOptimizedSolution> OptimizeAsync(GlobalAllocationContext context)\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.2}}"}}
{"timestamp":"2025-09-22T13:29:31.549Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:29:34.009Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Searching for method line numbers**"}}
{"timestamp":"2025-09-22T13:29:34.682Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":469174,"cached_input_tokens":432384,"output_tokens":3363,"reasoning_output_tokens":1792,"total_tokens":472537},"last_token_usage":{"input_tokens":40023,"cached_input_tokens":39808,"output_tokens":70,"reasoning_output_tokens":0,"total_tokens":40093},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:29:34.682Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Searching for method line numbers**"}],"content":null,"encrypted_content":"gAAAAABo0U8_i3AxvUnVL403IhqILMAHpMyivfiDtBvto0l_mY-aGr_chGNhZtpmQ7Vn_O_-6JVxpL-AwAYjdtvTk5z---cGLAZh8oCjJ9jGNTJEtZF_MuDT9yEk0DCpiOjrj18yIpb9PhvBbV58OQzw8MnADJ4UBfqVCu5ix6PSXf1QcxhUXTx4jk7DOe5U2kIYfliybg6zUXOV4oKXxnZeh-1x8Uiecox3VOQXG4BEjBvIif3tSQIEB-N7wbvqAv8UcwQ8ZnLWwpSxmz1SBWRI6-w4bXCPqrUUrxcSel84ZGcnbwcOrDcjd7IwWPNObZUf-zeZ8OEJjHKLfK2q2dMmlzEDryk9SH7L-AjELrT3rxBmnbpj9c71ITmqnXszhxCE0UqWKYCyyaGQP50io0DMPOjbfAkC5nLOo_kAkdH4lr5A35bvUlnhH282UAy6oclT8ftgUAP5f14hF8MTgP_616wzVxGVbHv25Wni2iEwnt2aRayRK6GMM4ScQfQd1hMM0_sMNRprhu5WpeKnc4XT9MsOYweqlZUF082buRUleN2_5hqawLdG6tXPJNeqKzjEL3qkoap7HEm9mPLHAx1DArA8QTv38Ea24WM7m81dcDEdDgvWBYP7eJEEd6l8Wh-oUhdeTz7GZPIuHHswqxt5UyEDFiC1bSVj07_DGeApO4gWWFrsjbsR3TTLi8kI9gWw6vwRfvO6ccPE0-qhdso0ogflXlJOlWST8aSy2gJXCYlzUDjdwDqHZv8tXHfMzHZUaCmzABPt_rEi8tsV3JuTgsW25fUrfz_13MzQLfyDTA3bUzPI9lZuXRdConBcoBRvdzht2CKK_QLTWBCJsPbfpqL-XomLMsEJ9YkJXPBzQy80xRC23_A49ZRasIWTmp50-DSD_0k2iIPI8W7LyA8yqPcBkTjiMsj-sfjW2RUl1jLrQn4yva0qcU3kfO4X8w5XkR-F6N0CEc3LeCmq_mS1rwleIfNAAa5uACaBSNtcp7d_6KW9sw0="}}
{"timestamp":"2025-09-22T13:29:34.682Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"rg --line-number \\\"BuildDecisionVariables\\\" \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\"\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_IyTAVUkFbEM4PdFecWOTuYiF"}}
{"timestamp":"2025-09-22T13:29:34.682Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_IyTAVUkFbEM4PdFecWOTuYiF","output":"{\"output\":\"64:                var decisionVariables = BuildDecisionVariables(solver, context);\\r\\n141:        private Dictionary<(long TaskId, long PersonnelId), Variable> BuildDecisionVariables(\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.2}}"}}
{"timestamp":"2025-09-22T13:29:34.682Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:29:36.752Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Adding line numbers to BuildAuxiliaryVariables**"}}
{"timestamp":"2025-09-22T13:29:37.481Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":509359,"cached_input_tokens":472320,"output_tokens":3434,"reasoning_output_tokens":1792,"total_tokens":512793},"last_token_usage":{"input_tokens":40185,"cached_input_tokens":39936,"output_tokens":71,"reasoning_output_tokens":0,"total_tokens":40256},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:29:37.482Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Adding line numbers to BuildAuxiliaryVariables**"}],"content":null,"encrypted_content":"gAAAAABo0U9BHf0pzKzW3unAXw1egQ4wfgPG_gQ5eUKYXp1mKjvOV65vI3LKtOQlkDLuNy2gBX_VweFVrtyq6PewebTIxFVbiBZAWo0AeNMCevt608SrzI6CnLiQLXDJsDXPWh6liP2pORCXFJPeerKsLeHaCvnwnRyW8S23lxSGjBfo2FyR9iKuZpwPohLsmpuxtRSETKO2g1krvcbX9KZZ8gN0BPi0QyHjFYBIjiRG1o2L1HmurOKS3VbH_NGuSOarpn229Gvz3yqstESKDaw7oDLa1p5XRAGSfHv63kWeA_2J7u5BZvijDWjWdhjWMqe0-yfppRku4pff4nOHWZgQG8myTBCe0AtwCzehe4qYHjwOAun6B636hlEIHyW0tt3vliXKbFTvAMIWE-kMEfyPReH9n2p5cCIxwgfbRHzqr5ebycjEI8KCP8gMdfdsfa0gYi7H9S3k9LZFT6qaC49oelwaU5toKa6JfqI9mxvsp50bTdyOFc9TtFHO86gRq-0mhtAB9jhdG4u1KTLaz1Nxj4f2J5X08JP6fiZf_z91GpGsrNoR9bbIL6xMXpe6BhUXFOaRMYz9L_RZ-mq76bu9BPCj0-dSQklIjinIlLDnhJ7rV3KN-KRgSi2auetBsMhrcfBsjcIucjvT33WwHFbhM49n_1yxhFXTcBSdu5NdcVBhRIkKRlnTPIqkLjVUNpqkDyYqHZRH7s25HgOhGaEhFr7M6kwqGIhe1FPWVKnr2X-0E7NakWOf_bWAHOvValDf9krmS9N6OQQTgsklKDKChRwKWtADTi3lT7w1lMIoaRhIy3dGlBXEIVkGQKx4HSycda7oVR06FaMtuOfUSA6B6QszOlpISHYlaWL6HLosP_5MXWXqXAEgilRpKpYmhHAlWZZHO6xndvSBOq1FBR9be3WvflqMGW4FHNZovGZGw4knCfwbTW4="}}
{"timestamp":"2025-09-22T13:29:37.482Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"rg --line-number \\\"BuildAuxiliaryVariables\\\" \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\"\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_vrc0l47vJ0x41cvhrw1izGV4"}}
{"timestamp":"2025-09-22T13:29:37.482Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_vrc0l47vJ0x41cvhrw1izGV4","output":"{\"output\":\"68:                var auxiliaryVariables = BuildAuxiliaryVariables(solver, context, decisionVariables);\\r\\n205:        private Dictionary<string, Variable> BuildAuxiliaryVariables(\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.2}}"}}
{"timestamp":"2025-09-22T13:29:37.482Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:29:39.457Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Examining AddLevel1BasicConstraints line**"}}
{"timestamp":"2025-09-22T13:29:40.140Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":549691,"cached_input_tokens":512512,"output_tokens":3506,"reasoning_output_tokens":1792,"total_tokens":553197},"last_token_usage":{"input_tokens":40332,"cached_input_tokens":40192,"output_tokens":72,"reasoning_output_tokens":0,"total_tokens":40404},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:29:40.140Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Examining AddLevel1BasicConstraints line**"}],"content":null,"encrypted_content":"gAAAAABo0U9EIvfLiPUVh_EPbbxKQm8Xi6Bj4kXW_r9YH6P5uw40oWxIOnsUBRxQNBaXl2LXEPohb6mDZb0kaie8mf3Fr1wPSnUXoTmzV8HdLuYV-euxkneDRRui7EKGzHFuq-8V1Q3DErYbwK7DWyWoHYzpF00BRH8S7A1J_ly7Cp-I16q6-LKrztfcAIzge4qpjN86oCpPQ7cJu3WDBXcyN_HTOQmVlmiALUOd3zJ_NIvNe8tn5_LBU9_pPeHQD-5pxOuJ5m9X84Gofns4MjU3l3b0HFd4ApvopRZfiF6nYcNkTJ_i2YAV1OBhjbGH4RUgOdo_JbhdS-wnam2gF3PYOviBe03RK-1EwfPeUd2aUYnlTaMgiKka0SjSJWm8FRIU3HjiGNBUxgitNyxfVSyBvOSYfjAVlWC5IqGDc9VoBclCUxx7ktF5dwjm62d-9i3LA8IxhQj5MTtVoKGQ7lCXB-D-l-dmLIcDQjs2peQR4NThPB4b0QlOz7_65a2k-kPCei31pgVHoQU0nJFSSHJs-rfrQd002oflsOFRluVo8jbnJ7Dk_WI-sUR341_5SCjDUn4HS-88It3UYNUrt3yOH_kXhJVU_YPtVedqPE2WCTWeAvWpFl8xfZ1Nli50zMYBBE8HTa8r9Tods--l9r48nyFQs1WJ_axnOIlQifXhsmTuPtr19cXWlrJvvi2LVwu8lEKnKxXh8KTCcbdpo9jsm5uGQFmfr5PVnF26SY3Bp12NvEExSypQyPC_6fCQ3LGx7mgKZd7rAFJ9S4ezeZNjn8c5dEbkWRZRCQgElAvgqpwuHeJ3m6BDRQjZh6Id_ZOebtX8vY5L03290hW28fR_F0D9kPPsXvktws72EGQytKqeLvWAKGpzanvUYD9Mj9tReHAas8oXnyhVQPTZO2ayZ5BDWZE_lQ=="}}
{"timestamp":"2025-09-22T13:29:40.140Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"rg --line-number \\\"AddLevel1BasicConstraints\\\" \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\"\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_BCwUwISVIKpCUg6hxowPjFPM"}}
{"timestamp":"2025-09-22T13:29:40.140Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_BCwUwISVIKpCUg6hxowPjFPM","output":"{\"output\":\"72:                await AddLevel1BasicConstraints(solver, decisionVariables, auxiliaryVariables, context);\\r\\n278:        private async Task AddLevel1BasicConstraints(\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.2}}"}}
{"timestamp":"2025-09-22T13:29:40.140Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:29:42.196Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Locating AddLevel2CombinationConstraints line**"}}
{"timestamp":"2025-09-22T13:29:43.222Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":590169,"cached_input_tokens":552832,"output_tokens":3578,"reasoning_output_tokens":1792,"total_tokens":593747},"last_token_usage":{"input_tokens":40478,"cached_input_tokens":40320,"output_tokens":72,"reasoning_output_tokens":0,"total_tokens":40550},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:29:43.222Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Locating AddLevel2CombinationConstraints line**"}],"content":null,"encrypted_content":"gAAAAABo0U9HBOCGpde9a8w3TmNKzWureC92FYbmlr6j_OPlgxkISul9E1MNXElMTOKnrKTrQWSx9cx_vOawQ0NqKQkq_bU0y87F4vt7iBs9waXuTiPpFgvmF-_DOPQLQHipPKtH3XM_o9RO-10ogKl8IfE4U3SmSVXbT0_2v0VnMjPMc4fZsxTVkdmGRDGZ2eUnw_cvVaeBJALihgjEu_Y6MfJXkBPZLa2CqDmxjiXwUvNsXMp2_A6NXgfWiIdzgIU5Zjb9nGPUZO9SH-mL-3qygamWp_kEs0QiqhaehSvnFrG7nCbrM4gszoXA9MThr7kWFlklIENY0nibimMu8MQKoT6wOVhOphHc_uZSKP0pDAnIDTFZWNIAiKL0pceWnGYJb9uQf2-kqRLZkbmWpCf1prfbAlbwfl7PZh0Y62VLnmSIlOYTxMKQ9MfFJXAlODwFfSUUR9ryTwTXYph1BBXmytNPMX1-mAnNfyT8w1X4GgYhW8N9GT9lUBadVQlYN253fOBy8EbQBsvMMl-Gdkz4LiUfImw1L9GWTM5JkNEmPl2sqbvImFwjR2-cCEMo-wjfgI2jJC_KtubIWk0wxoIkYLUL2A7la95oBb0FY-8gwQcPbH2oXu2e86okFNhqJP-mMMECekgorgLmUbogKrqmf0iBRMsCfmuATB6tanDjwrhrfM8vYp4ssqwUqsoLHqFE8Xr25knacxHtE1DK3gpb0OlBYkd30KSJS9uWTe7RQkcgLUJola27XipqB_PCuF5wTHAAUUV1NMVzJN7V8HDtdnWI10sadShauCLBd1MeRzcfpc22ISfyU5eHrWdzfksi2nZGYRpGia6ljrRr14-tzpMe4y3gx4MPBs6VtNQysYWcIi-gR53Ukj9BNmtTG1heWX-JCU7PlwlbUZnm96WGbYJtBPJBnhwoqkhp-1O-Xue8B8chm_4="}}
{"timestamp":"2025-09-22T13:29:43.222Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"rg --line-number \\\"AddLevel2CombinationConstraints\\\" \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\"\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_zwg9dZmEjy567IV1x2bG1InL"}}
{"timestamp":"2025-09-22T13:29:43.222Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_zwg9dZmEjy567IV1x2bG1InL","output":"{\"output\":\"75:                await AddLevel2CombinationConstraints(solver, decisionVariables, auxiliaryVariables, context);\\r\\n382:        private async Task AddLevel2CombinationConstraints(\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.2}}"}}
{"timestamp":"2025-09-22T13:29:43.222Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:29:50.861Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Identifying target line**"}}
{"timestamp":"2025-09-22T13:29:52.676Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":630795,"cached_input_tokens":593280,"output_tokens":3650,"reasoning_output_tokens":1792,"total_tokens":634445},"last_token_usage":{"input_tokens":40626,"cached_input_tokens":40448,"output_tokens":72,"reasoning_output_tokens":0,"total_tokens":40698},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:29:52.676Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Identifying target line**"}],"content":null,"encrypted_content":"gAAAAABo0U9PACUBSb7aLQVNURGH7eq6ViGkKEpVjjZdzcrx_wx3S_mt30SEXOOMM2wUoE99001Jr1yPQZ0nn5jlZY0gDN0n0R5bDvlHnZXef98N_6EHZL1q49YUQmV4jhIq4SdwuPXKTMGn7GGig-O0nT5WmG6fbC7jWkbjJEZS4G6TXzmJ9sxP-43u5HNKtoc73-jM6I-otMzasGS5NVfggylBIZxIvLnG1DeXt4vvujj1-x8o-UuNd5r-8ncSrw1259qrlUpigWfDVP5UJdbzumQjwc6A4iwkvGmjxQw0lfK7quJWDMGXI74raT7Fbrx7oqXBLYSzU7vAOP7roS2E_yjRp3GsHZ_1pZPk0zVChZhLjeXiinr-NVr6I92_48djhfvCqkRgFyZA_kJT5ZWFsEQGWRbPD_wjRRndHZmQLc7Dv31TkwMOPU_G1VicVtQV3KRM7wQ4BfEpJ25-l_oIUpmBlbNRU_ROjHlNXXMvBweaovXTVHiPhDMOSHEOZhkhkMZTnpKxg-kjtAfuLuxgEalv4l-8SLDmin8AfuJjgUCCI7NJCFLz-65reqbbc0P0zxnevBWdybw8l3BbFR5G8YOsk5BN3gBDGjRblEvYEcv5bxeIx3xkt75T8NgnUOdZlSsXgSb7nAU_V5L6tm8rj78pJeWdNnUCJ2S3GcZEGSdyibNcCsYp33vYQVFQB4XpGSyObdlN8mc_-St9gbeLE0ZNgdMqjNfKYaZBMWeHTcxudSVspCDMs1oAfsI3CPjVbSuPaUoybxXyz6Jn8wnhydGim443GkAd2qCC62VdYgk9noHbNWP-14UYpuY-GUjbHrj6m_OUVqAPxvOkDLCebI07VOFoGT-QhIo9ZWc-gnJLMjq_00beY1pKeULwu83FCdMWHE_dySyvmQtUVvKBWUpQ0w_DFQ=="}}
{"timestamp":"2025-09-22T13:29:52.676Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"rg --line-number \\\"AddDynamicShiftRuleConstraints\\\" \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\"\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_ydkd5emyQZQht6Giw77HoQTr"}}
{"timestamp":"2025-09-22T13:29:52.676Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_ydkd5emyQZQht6Giw77HoQTr","output":"{\"output\":\"393:            //constraintCount += await AddDynamicShiftRuleConstraints(solver, decisionVars, auxiliaryVars, context);\\r\\n407:        private async Task<int> AddDynamicShiftRuleConstraints(\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.2}}"}}
{"timestamp":"2025-09-22T13:29:52.676Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:29:54.778Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Checking for duplicate AddDailyWorkloadConstraints**"}}
{"timestamp":"2025-09-22T13:29:55.713Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":671573,"cached_input_tokens":633856,"output_tokens":3722,"reasoning_output_tokens":1792,"total_tokens":675295},"last_token_usage":{"input_tokens":40778,"cached_input_tokens":40576,"output_tokens":72,"reasoning_output_tokens":0,"total_tokens":40850},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:29:55.713Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Checking for duplicate AddDailyWorkloadConstraints**"}],"content":null,"encrypted_content":"gAAAAABo0U9TgxpLDZgtjUNELL9NpVVNv2MneFkC30pwnQyP8bH2ylSuJs6jYTUkXf0VdYHnofaNbApBYAZeJBBFrUBuT9eIHCzxlEaneiklA9zWa2vNAI0Jb-J_EuNiYwG085Bi0Cohtw1g9xiQGLIGdNfLcwBRYB8usnP-eUx31xpbe7Rjqm2gyXZPLyiNK-WuWO1isQxeuPjog5_R59oW9ZyZ6CnxOkuUc4dgoeulshS9mDatv7XNi4KXnMAVfCm-AHI-f6VGT6Yz6eAu3pJF3a0MQHE12Z3lLVcg9J8Em_iexU8Taf-Bcn_GErPHGOUjEFvlC5WfgHuaZ7nweB0e3bsDDxpr-wH04oHkC3wORChsvltzYHCDozMaJgT7jRxhWIpr888Kd9XhxhsKLkJBMlugpLjbRWgfpAy7FWBVyqaPTjMPSB_0PzNuNMTDJ9_Fx0qveEUjtMJvdEhnSsqZdvBOLfrD0nvErpENw7vxcKQppalFg360HHnsWH6daX7Z5MjMx7IaUPY29ED5C0Z49JEmaqxsNitoOA475NRFp46GYdcCRuh0uZLOKYsgTv3mYlTUubdb8WuT8uiF1tSoVkLZloJSDtfHpefyzY-ImLogT09VCFpCZ-dNxXrnPNmw8f2ZHdunsO-ZDh0hPVjG5haUvlbjKn2rqp1pYmohpzxw5qKNwHFUr2PKIVX8m-zUnPSC8e0d3affaVyScNSrN4Hxq2SMsn1kjDOywM53XI7GAuArEcOUIeJiFe7rx7AerJZv0wQvpEXGQk88xluGahrAsoOpbCx7VSLbQaXT48g9sbzHEo-WI1pbe_urfjmQghhrYRmYptENKh9CEvRnz9TNqZ0YbhrKZjq8sMvA6d7VRT2aTXU4af-RJBeOvVAwyH8Mi5JxEpG0QXCFl1oFBFXuOMSVm-guM5H2mpToV4ffvAmVm0w="}}
{"timestamp":"2025-09-22T13:29:55.713Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"rg --line-number \\\"AddDailyWorkloadConstraints\\\" \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\"\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_Fsh01Y3THuPHdZbuMbHxlFJQ"}}
{"timestamp":"2025-09-22T13:29:55.713Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_Fsh01Y3THuPHdZbuMbHxlFJQ","output":"{\"output\":\"396:            //constraintCount += AddDailyWorkloadConstraints(solver, decisionVars, auxiliaryVars, context);\\r\\n531:        private int AddDailyWorkloadConstraints(\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.2}}"}}
{"timestamp":"2025-09-22T13:29:55.713Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:29:57.758Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Noticing AddLevel3BusinessConstraints**"}}
{"timestamp":"2025-09-22T13:29:58.695Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":712504,"cached_input_tokens":674560,"output_tokens":3794,"reasoning_output_tokens":1792,"total_tokens":716298},"last_token_usage":{"input_tokens":40931,"cached_input_tokens":40704,"output_tokens":72,"reasoning_output_tokens":0,"total_tokens":41003},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:29:58.695Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Noticing AddLevel3BusinessConstraints**"}],"content":null,"encrypted_content":"gAAAAABo0U9WKqvx5U_uN8LuThws1KFCFYsOqQFrktr9Yjqq-s8UaVgjZ03IK1FU3AMAi_hf_e25kWhqOiR3gw801DIi2qbP3yvcpdp0_QRsPpHb5ORFSp6u8tS8dV8xD0MfnmPAT2Valx8zamtxfcqkQH6i7sLmhHBI2xLHXydMAtyn6VtW-5KGjeselREEifJ2qgJ9BOK6yDS_uhqq0kfqumUVu2yIa05zNrscVqIGtj3hUxs8kU8dVuIYzgJdTRdrz3g80H4U6O22G7rqJiUs9tOpLcPKxSzvmuUfPngcbA8sGXE1w8ZH6rOwn0y2o8Mw9M1kotnQPGJEo7BwDX-osh6pMgZX1nFPUnoAHjm9bXBi4NyOaQBriRYd0pAr7tR1jGAi5FKRIml4H9m4Av2ollrbgMutLjcl-unMJaabIibNteRyLpIIRLxvaitNCn6sRj6oEKb3WeaXHO6GA_ukj1WLQdlaVY0gvxGBfJns805EuU6Ljo4yweNu8ONTAHCpcT3cxvNgnkpyCTRMvBtaOYslGWSx7IV1ajcTPma-Ye11bj19o5N0re9MTJDuYYuMHvGIjCpLre8BihVrWoCGXbUdi8E_lU-6x4KzLfLuogWfvJ1TlRRoJJ19sW0mCY-Pw4jK3-pM49-ILq62eDCjSgSy57vj6iPKbq55AlZ-4utJLKvi0IWw6zJn5pGEHM77bf_DyJQE0mV-49y2nxUzPc2_eT5u38UQkedLxxWWBKaVuDvVD0nEyi7VFoU4VDneiIL_2N4nEt7D9hH4j_fHifvAXQuo7BDreWnuVxxFijy84T94xzyAQG1a_AZrC4tcdDl8zcto9_GX6TiasKNQnlbS0zN8phj7tIh0CfczvtqxpbpFNzeKorKmLmyDm1tfiGqlkvt_6e6_wu_srlg-Lhqf_ExfuA=="}}
{"timestamp":"2025-09-22T13:29:58.695Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"rg --line-number \\\"AddLevel3BusinessConstraints\\\" \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\"\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_LJ3uGya0sPusVVogJLAo6Bml"}}
{"timestamp":"2025-09-22T13:29:58.695Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_LJ3uGya0sPusVVogJLAo6Bml","output":"{\"output\":\"78:                await AddLevel3BusinessConstraints(solver, decisionVariables, auxiliaryVariables, context);\\r\\n576:        private async Task AddLevel3BusinessConstraints(\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.2}}"}}
{"timestamp":"2025-09-22T13:29:58.695Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:30:04.581Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Noting AddFLPriorityConstraints mention**"}}
{"timestamp":"2025-09-22T13:30:06.013Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":753581,"cached_input_tokens":715392,"output_tokens":3865,"reasoning_output_tokens":1792,"total_tokens":757446},"last_token_usage":{"input_tokens":41077,"cached_input_tokens":40832,"output_tokens":71,"reasoning_output_tokens":0,"total_tokens":41148},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:30:06.013Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Noting AddFLPriorityConstraints mention**"}],"content":null,"encrypted_content":"gAAAAABo0U9dTdo_bXqp_J5goEW857Hz4ZGIWlwrAq0NMO71Dwo0R0U-LnCnYPnmCCABJuRNAJ_G57yZLHdNIUKP5gFO4BxpHD2gMwp4dGu6zNo1ZbtU3evEiJ1kNhlbIPSnu4OnrVwuClfdnwutBnwnH-0wzXZ3t-GUetJ-V5B_poqnnvq0tVCXzbr_A8M1U71wn0PqFcNwq5AftCyVR0VzLlfu7Dq8bVOG5InS8CInLrur3-QObbkR8IDi_bA7DRjIjCayUBiFMSBsm0sOOfG4h0kheLgzvZevm1nPh_Sn_iqYzZeQ5w5-JuNZeDCUgkdV9Q_2dE9ueUhbb55l4H1ul4W9SufXcXjr9RH-9JZDeD8injs_cKOxL6_Jm1ba3LcpJDod2J4_uKUDvMbRAn4ty5y3eeOCtiEoDLoLuhdGUKJuTtrLDCG3YpsISLCixZbAT02jEfT5rwRKpj6fDRbqi01plj0qnCAnV_5Dbb7zCS1VukPxkXlK4po4255kWE64amEhEiwx84zhWk7vHuGhWhLVVsnAEvJx9MqpJSX38YedK3EcTZ4zgFz8DOFrNHHDKVlnEZ15vhCF7pvc1m5MEIwA8jFl44guVDVkA68HM2JmeLRL3vNJc6CvJA0ng9T800KKVBHtqZGK7qmxyrv4QVxjXYHXAbHvZMiZL0cEeUpc30BAukPUbxMYdRAYsh0jIGbn14HK-KFQpBr-5pRo6pHNeI071crgJ6SMqk7jlDn9SLyLr73xhpu7bdzMLIJtHbVI96XdtQxhjU6NWwp3LJvdML-IWQx15RSKomFxHhcaVscD_hYdFnKc3I2bTYXLLSSZZ6m82L_9TLesRp4ZuhMHtJqJOoKycjV7tDC4lMntPYDViL9sQYKL_0x9LsK2YOz6DdwHxg3UxyrAUTPjbOldNROF6A=="}}
{"timestamp":"2025-09-22T13:30:06.013Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"rg --line-number \\\"AddFLPriorityConstraints\\\" \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\"\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_K9rtmaRWMDqRrNaN5BxTSyEf"}}
{"timestamp":"2025-09-22T13:30:06.013Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_K9rtmaRWMDqRrNaN5BxTSyEf","output":"{\"output\":\"588:            //constraintCount += AddFLPriorityConstraints(solver, decisionVars, auxiliaryVars, context);\\r\\n609:        private int AddFLPriorityConstraints(\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.2}}"}}
{"timestamp":"2025-09-22T13:30:06.013Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:30:07.928Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Noticing AddSkillMatchingConstraints reference**"}}
{"timestamp":"2025-09-22T13:30:08.806Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":794802,"cached_input_tokens":756480,"output_tokens":3936,"reasoning_output_tokens":1792,"total_tokens":798738},"last_token_usage":{"input_tokens":41221,"cached_input_tokens":41088,"output_tokens":71,"reasoning_output_tokens":0,"total_tokens":41292},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:30:08.806Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Noticing AddSkillMatchingConstraints reference**"}],"content":null,"encrypted_content":"gAAAAABo0U9h1hnKf-ogAmzyyuQcwFRrhqUgQa7juMPG9pixWLs9rKPZJqNWkpYusvnAcFl9xIqSgqqUIv36YBsAkAVqe3QnlSPPTm1jsey76PNVMRSsVukjKiSwfwLYwVqGppjVJkAKLODsSy2kPb-VqVqqKOSPS3twgpy0vQ6qMoaKWM14vjseuWXZ7YLNjXCLf2tJrQaZKLYJHhPJyI4vrSsGOQ3_3Vuq8D8NTVnIJc3j0F9ab2IOyQ7LglKV-LJqxMYqlNUNJZTTW9Ld9kEfI7XUJHUZLcISLsGp-RJTXhYrkRxekoYI5KU8dUsTfE_xYJkof_lM1AguIUNoLqblcXA-9kNqGppZkFxQllAbcsmKsHneYIwX2ZF_wUi3uEWzchT6qJGblW_g6IH73bEMWBraQ7o-yxn_0oX9QrBN4YS9AKuBzeXv_J6sfs6PTyGa-3j0SN9XrXk4QiDHqKBwjHnbzE05nytlZ_bWRyrBf_knA0q1CIRQtovjI3WJ9uZeWe3WJ91fL-f7LszWNjj2mX4c2WGTHWvVPnjUDqQq4RvneBCAVcLFPk49QEU5PitEkeKv4wij7C-eXXRXQtv1co2XpGN3aysxHGCACGx8zF2396QiPdOXRwAYHLrNzn8hkSGET1vcs709MeTaN0U3B_2EWDiWJPqh8TNt9dWh8EEodW42tGuGvnHSjHB6BnhkzP3NaK3NS_8wr8V_A8OHFnqWLwaXWnbgP4gJhp8PS_VyCdAbbuw92DwNTARG5jVEqeb7n8Qn6BsrzwwgxjvaeECJhH_HDy5W-EZPnKuVbDLtonwtHW2ca4GDEO-FOgP8DJKoLLsGS6OUEd6iw40Zriw8LsaqDW55-PB1ndrkzsQf7L3D-0un-7S9Hh3s5efdqRlj86G7iyj7BC4XcvbIrLBAOhQ5LQ=="}}
{"timestamp":"2025-09-22T13:30:08.806Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"rg --line-number \\\"AddSkillMatchingConstraints\\\" \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\"\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_lyH2pfsfNJ2njwK0ztwOrikq"}}
{"timestamp":"2025-09-22T13:30:08.806Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_lyH2pfsfNJ2njwK0ztwOrikq","output":"{\"output\":\"591:            //constraintCount += AddSkillMatchingConstraints(solver, decisionVars, auxiliaryVars, context);\\r\\n671:        private int AddSkillMatchingConstraints(\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.2}}"}}
{"timestamp":"2025-09-22T13:30:08.806Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:30:10.878Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Identifying feature name**"}}
{"timestamp":"2025-09-22T13:30:11.510Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":836167,"cached_input_tokens":797696,"output_tokens":4008,"reasoning_output_tokens":1792,"total_tokens":840175},"last_token_usage":{"input_tokens":41365,"cached_input_tokens":41216,"output_tokens":72,"reasoning_output_tokens":0,"total_tokens":41437},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:30:11.510Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Identifying feature name**"}],"content":null,"encrypted_content":"gAAAAABo0U9jcNATJ5IDxwwGZ_YNVITJtWRJ0DTbbghyyvCZG8Al0JEiOik9WZi5SKdJyxgFDm8VlqQEbJz-o9jkcwqRWgj-M-CGqmrWu9qMw1Q0A7yNqBueUMm42k_S1DAsarvpR4fZJE_HAEgSkRJBr_X4p7kuvQtW0ubjAdPRNyLE3b5Gz3Wj8UsrpA7WoD75ZNL_y32o8f8i6M2S9xwuUjSEeuZsNX4OVMk1QvWx6ueqHEfaQ6UaYEUlQxlNGHyy5RJiLGHUfZUhcpKLoSHG67wkCrDZ1KaR7SLCiBKkHGgpcAIODeBnI7UHqOwSp7O_i4TRzXM2S-3x0nepIxuqFOFZbcS6-iEQ2B7KtRQkz8zyTVdsEmR2DqyWM4nn8ecTywf2cmGqFdRdtJtnmhx4ayJ76Kfqbt0S8PM8_bngSNMFAf1gKbKuIscaM-LpsSRXsd4PVB0X0cx_KJ-ZruKa00y5_YCGZuwWhjl4IdiCcwKNiLOji8TvX4AHOBDYxXE3b2DGZHM11I1y0alYhhM7VG-ih9jgKfgNiI7xJh0ATqkUF8T7cVDH7rdBft2sStFzpbrD0GmVf8LR6EkdzT1qvO-IxLuM9VUMDbLDqK1wIV3hvfxtf-ddIke1w0m2pODumZ8hxS6xVhZtmgWzHIHxi56a9AbDFryK99GjzGp60qxQJfTh6ol_vvd8XoaO4EdDylGoz5YWZYL3i5TPCtMaMoa1gdKEsd9MJj7imiQDeWrZnbSDzioWMOmhLkQiEop-dbwTS2FWUalXHV3dhTLeDV_-OaCZwAEa9Zc-qe8lwV50kwpBcdWr1az6HYv6n5CACPIShfh_tEMlzmnDzgO6UdpG8JWqnFoiaikj5B_Y8AAAXaf59eaFrNWY8I1D6eNWZGxQLTaxOR0W2eiQxnwOutwTLHsCUA=="}}
{"timestamp":"2025-09-22T13:30:11.510Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"rg --line-number \\\"AddProjectContinuityConstraints\\\" \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\"\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_OS3oDVc5xexgvgYmX3taLkkL"}}
{"timestamp":"2025-09-22T13:30:11.510Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_OS3oDVc5xexgvgYmX3taLkkL","output":"{\"output\":\"594:            //constraintCount += AddProjectContinuityConstraints(solver, decisionVars, auxiliaryVars, context);\\r\\n709:        private int AddProjectContinuityConstraints(\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.2}}"}}
{"timestamp":"2025-09-22T13:30:11.510Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:30:13.444Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Identifying class or function name**"}}
{"timestamp":"2025-09-22T13:30:14.123Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":877678,"cached_input_tokens":839040,"output_tokens":4078,"reasoning_output_tokens":1792,"total_tokens":881756},"last_token_usage":{"input_tokens":41511,"cached_input_tokens":41344,"output_tokens":70,"reasoning_output_tokens":0,"total_tokens":41581},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:30:14.123Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Identifying class or function name**"}],"content":null,"encrypted_content":"gAAAAABo0U9m8Lt7KuZ77yyUf6A6-USuR_ofXGOEeWDeru9tUUedZEd1H35w5BYiKshCGuw5vjVW3mc8mTPy8WvbXL0CPbomNGpHVQyZH5TH17GEEdCRl_uMOhp0PgaEvtF33IgMlqEvv9hVzALqTb2AbabD3-kbw2z553IYyTrnHhV6AUGXXLsR2TYYrj_FPXJxUsMvRPCkB6LbfvdMKRCNsowzDWzn_ecvdeWH6rDDboRCm6NhljkSD71lMvraqRPaWVGUcOXzX8awWZJyq9PUCchoFec3xGtQ7uZEt7vb0V__WA26JSfy8hMeyO7jYxHSbwOHf_dENHAAR4grqGSIARyf87eBEwT9_2K_dso1Pz9zlBuBZ9X2-m6yuzLVdWOt7GunIszbkji9U0HNkJZ_qkboV8iRumOYbONNLtRthgIasDrXcL5wfaTxJbOJrlgyO3SjLxgGb1I7IWsujW3xIhGC3Y2g10M84RBLg3Bl-kBSgmn1FZzla7CetfHR5Z0ZpG-YBW-Z9FQBpyQc7E8AC2dYvmdLdJS7KLTJ4JzYthLdObJUuRpw1pscmiUIjkIXe0Iv39hx52ygzMBeIWC1LlHLzeOjXW_cVjDHCguQmrBuf5A7ZT6-cy4Mns4fKR-gIciaiSwOUI_5eJSeJRXTUFgHOVDrzhQ2J7FB0cmmUnZ9hcrVqUBrW8lxya9qyPo-xpMXgoLY0M_jYg01ESUmiIL0UP-xxbwZrnW9iFffq5SJ8z_Tma7y6JMDbGdLrwusMA6rLTdngS76qJZh4cS2JosaOPdCww9MAn-j23JEjj2_o_eZof_GTB6mOlyqL0gDghKSahQ-4obvU7sGKoRy1NAe1sW0ekijgl6JQe2isV1cQuVNYL_72zyw6NcAjDHsVXBxFhC_"}}
{"timestamp":"2025-09-22T13:30:14.123Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"rg --line-number \\\"AddQualificationConstraints\\\" \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\"\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_KbFGnlVX2PLF2WMx8Vk8jShL"}}
{"timestamp":"2025-09-22T13:30:14.123Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_KbFGnlVX2PLF2WMx8Vk8jShL","output":"{\"output\":\"597:            //constraintCount += await AddQualificationConstraints(solver, decisionVars, context);\\r\\n774:        private async Task<int> AddQualificationConstraints(\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.2}}"}}
{"timestamp":"2025-09-22T13:30:14.124Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:30:16.735Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Identifying function name**"}}
{"timestamp":"2025-09-22T13:30:17.537Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":919328,"cached_input_tokens":880512,"output_tokens":4150,"reasoning_output_tokens":1792,"total_tokens":923478},"last_token_usage":{"input_tokens":41650,"cached_input_tokens":41472,"output_tokens":72,"reasoning_output_tokens":0,"total_tokens":41722},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:30:17.537Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Identifying function name**"}],"content":null,"encrypted_content":"gAAAAABo0U9pgmDsr6SfzUjE_OBbCBvnOi4rrwR0So84Jiw7_wqjBSljHO50Cl9LCpxV2VlYpnT3K9vNcBurKRAy0cjSp2SiC4xHUZYGHQN2WyFvdkLRxGf-xOlRUkVOL7NAGBuFpo1IRKmgQ7bOtYjnEgeASR58zq3BrpQByq0LohWJe5WWbuxHQC22pAylzLyY02U1V6ozvfzwlY7KTW7a3lyIbeKNJPtBmJWT3WH_oCTbGmIwckZTxCUKJCLRW4sc7sR6vMJuR-4j4LoTwe0c2h03RqWXsZ6kXvoztnAeLGJj37z9ooBH_o6XFY6vqaAFq9QisEXsgAnux9Xm7VbRdoaejQo92CHMRlIMGmL1RrlMlhidA0UE2rHnVl3KbjtBWl14q5SNticFydzoJvQHhvJClQTgq582RbFiY476Xr7hLV-fzEp5XpW1fcTOoEPi15JHq_D-N4kX2ej7mut2rlYeNcsVKOFAvtsNDAd1hMNBn-mWnZ8cTMofZ8A2LMTEdnUqSA3WNpIXh47cQNYG4wKm-97FStxEFP8lYwHD3mQatWO72iqj5vvZOmnVF7VQYoEpL26y0seNBpFrSnLaiYVdINA7isYE66g-_BxemNPGni1CeSUIWLAPKtRbk3LS5xTqVCsCaDEIWj_qg5gFWrFnnAWA0i6H9KdLCqEQIpo7ZfvFMT1__vTQqjSJBmakDaywVSCExfn-mxc0VxA8Z9FFPU4xmcWBXpc3sDSgUTxNXfo7jEl4aiQ7HXiJAbSC8qrSEykGJUvFvY3k_VSIVUSbjTK4Je3iNOlFwQuGlZKwpDq9xBRyhPal3jDvESgkakJ2dA5jfRuDE24H3-gUGdtZIjMZVHJsNJQmhRYUOm3Eg7jcaM-nj6HRwqdjCsuOtMBDUWrnsLw7A99wERgl62kL_hnMwA=="}}
{"timestamp":"2025-09-22T13:30:17.537Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"rg --line-number \\\"AddPersonnelUnavailabilityConstraints\\\" \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\"\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_Fm2o71Q9JOc9KNLeT1X1rZ2Y"}}
{"timestamp":"2025-09-22T13:30:17.537Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_Fm2o71Q9JOc9KNLeT1X1rZ2Y","output":"{\"output\":\"600:            //constraintCount += await AddPersonnelUnavailabilityConstraints(solver, decisionVars, context);\\r\\n2192:        private async Task<int> AddPersonnelUnavailabilityConstraints(\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.2}}"}}
{"timestamp":"2025-09-22T13:30:17.537Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:30:30.455Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Identifying relevant code segment**"}}
{"timestamp":"2025-09-22T13:30:31.182Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":961126,"cached_input_tokens":922112,"output_tokens":4221,"reasoning_output_tokens":1792,"total_tokens":965347},"last_token_usage":{"input_tokens":41798,"cached_input_tokens":41600,"output_tokens":71,"reasoning_output_tokens":0,"total_tokens":41869},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:30:31.182Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Identifying relevant code segment**"}],"content":null,"encrypted_content":"gAAAAABo0U93li6gMPX4bK2IppsQIIa1HNFFxePol1tqtbiaw5pGCxchUtHTZLxAYPc0nQ9Jy11cqqIRku_W3Jh3XRwH5spcMwoCi4KrFzvswTNWrfV9GShzwKxX2isssuGyfwR7b6P1ahbrdTWn9UKwpIk4TqZT8ImD_9HzwrbqEa0_MvU3cwNsYW3Wdtl0aARJ6OF783gVCmKPLbfL1R70-KVOpHw4iTG4OcIzc71jl_hpbv2ZABwCEh_PL1cY6hCr6KH-cltffuITPcc7GEMw0VavWmRm5C675EYjrNd7tFKFDSYgOsRRvmVzI7b0rzAy0JmWWotrHS9lQFhNMtQqrspZEFRnqKmIMJXF2b_LZMvxd5RAMwPVUeClo_xhsHURYFJVoLadopVXY8E_5497QJ3Pu9kxJ8vrV9eiMWg3kwJJ3G03AOThillzIpb6tMa-EmpCc5V_9h28rx8pLSPeh3L3Q28wGr3NMzsM83Qm0ovp2dqMrgkJvAU3R3wKRMZJoeVLdvvPIbQqhgU2v2AO_rD-Qe9GOm_DmYQcG-D5WX9OW1jyr_YEUzwLx0jpbPvEqTymxLNROJ7QWbt188WUgY3yY8IgkNG0_BCEnK_9mOfqIrRau97QwSeRrwnJpb_l3OU-JYzl0MpzCphV-bYFmHngsfWMNJVvXCxkxYmnXz6DjtSMWNMQAIQQUFer29G5_MmWHnwZEFZznbqZSt7CPSi-j-vzZXH6ASlrT3YviPOMaBO4lhAQvwPqqlOznW7pM4M7yhZVUqGlyHRZu89i70ji-1rfjp7ItuBwW1DJqBFnbo2AXl6uqtAMJZx6ewx2IPAIM6y2ufTgLUe-fAtVgZQisK2BXnmVs_yfbhBLwQm_vtdoOdD0J88M6lautt7gU_4NCxabj1ir24fmo75dM1YHh4ETPgzrYsSezCzDzMbCTryh-SAJj-RQrTh5prqfHnQjubz9U-s35yRmUgmtlu2BQr1X9Q=="}}
{"timestamp":"2025-09-22T13:30:31.182Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"rg --line-number \\\"AddFairnessConstraints\\\" \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\"\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_rkA2a928yuZA5jn12q3Y0DLk"}}
{"timestamp":"2025-09-22T13:30:31.182Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_rkA2a928yuZA5jn12q3Y0DLk","output":"{\"output\":\"81:                AddFairnessConstraints(solver, decisionVariables, auxiliaryVariables, context);\\r\\n835:        private void AddFairnessConstraints(\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.2}}"}}
{"timestamp":"2025-09-22T13:30:31.182Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:30:33.071Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Locating SetEnhancedObjectiveFunction line**"}}
{"timestamp":"2025-09-22T13:30:33.649Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1003077,"cached_input_tokens":963840,"output_tokens":4292,"reasoning_output_tokens":1792,"total_tokens":1007369},"last_token_usage":{"input_tokens":41951,"cached_input_tokens":41728,"output_tokens":71,"reasoning_output_tokens":0,"total_tokens":42022},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:30:33.649Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Locating SetEnhancedObjectiveFunction line**"}],"content":null,"encrypted_content":"gAAAAABo0U962Daf7yykwRoleMH27G5xEotLVzr4tcBxQcEhTu46f9m39u6I-vAkrJ0bgVk3A37f8z9OjtGfhqdTQKsVIaMWamiLR5bCH9P0aKs5tUWgDmtPqJZ0d3GTHBEvKduqvw6GSj1aKPsMOqdv2LkbRccpyOWtvxiLr3YWdc5d8X4DLkAeO0Xk5ZiHtJP__d6J2MjEFhmQf6ZnhVCZ7j7Rs7WjXzgjDa3z69FKVQpE2CHflINOs54S31_XlvsRsgYR64PHZJ9JL2DkZMHoIWhzpQlzGpW5ZikD52CUiM55QxGMUJyiBdbQ-tFXlwndZga2ite422N104mhnhO4id_0XZN-s9JzH0KE-Sk2ZlnPW7wZjeTDkanmLhurss4yyAu3WRSq73IdanPpc97jYNaLbrG00yMy7zbhrGVvD-8NimknA6M0PvEvQmbqOVZnK87xSiNuH0HD5WrtQ7PBnAuHKNXumuFSF_lRDii_GBrh8IIRvrhlodFNhGx3kARsijZPfnnMmBYvNpgzmUVFos5f-Iun-6Rj3sB8md1d98An2CZHupqTauVugPVcYA5wL8Ddei7IHjKuj8AXKIP9QpJ7fR4g76-GXw4D3N411h78cvEHcsGJIcOHSEvZ37SfK4wekMWiqa6cdsWhQpKTS7p7pRhv7EILyq4kk-wHt96-lTfTYeuQTeUV1R3rzUOXXXYtkHYfEz_OXVwWTxql2cspJPesgbZlpEfByOJ_8UAq8PSw02PFrtriLkdouuU5jAa25QtthLtLk68QqAOhHv0heboMMd5O2_vpzQj4fSJqa0rivBF8TrTY8_BTHI_oCk3fsZ0dx3tFFnd2XhMFF6H7WCpnL2dt-GAk0C52Kf82wUhtwspWXiScqNdXTjRCQNwKnBd4kPLa7C6ucYvX7iopautIcA=="}}
{"timestamp":"2025-09-22T13:30:33.649Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"rg --line-number \\\"SetEnhancedObjectiveFunction\\\" \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\"\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_FsjN8qNps0awSpJsXYvFnNJr"}}
{"timestamp":"2025-09-22T13:30:33.649Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_FsjN8qNps0awSpJsXYvFnNJr","output":"{\"output\":\"84:                SetEnhancedObjectiveFunction(solver, decisionVariables, auxiliaryVariables, context);\\r\\n932:        private void SetEnhancedObjectiveFunction(\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.2}}"}}
{"timestamp":"2025-09-22T13:30:33.649Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:30:35.796Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Searching for AddConstraintViolationPenalties**"}}
{"timestamp":"2025-09-22T13:30:37.494Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1045168,"cached_input_tokens":1005696,"output_tokens":4364,"reasoning_output_tokens":1792,"total_tokens":1049532},"last_token_usage":{"input_tokens":42091,"cached_input_tokens":41856,"output_tokens":72,"reasoning_output_tokens":0,"total_tokens":42163},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:30:37.494Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Searching for AddConstraintViolationPenalties**"}],"content":null,"encrypted_content":"gAAAAABo0U98-HCJM1DkaskVpUfnSijck60osN9JE6wt6otpbdv4OsKN3YuESB-9ba2c0w4jAyoWyqOwQ6Xk2EK0yw7I9wjgPLNLSt1aGdPOHkB3vDVmAr5TZpczdJsU1vWh3lz-N692Njfy4L99vPbuyJ93oi3VhKIxPsncieeRm556MizQXy6Xz9RAblt1D0t-u41oZFquUJvQCBHgbUMnwsV7Vf9JT2tWI2sCCf54M42D5xfuEbNVne4w7t97onC1rrdrzUVPkGSlNqyePcaj03yxS2WpA0TM1wecvig0o3dkWb13ibr8UbC44dQcEQa_hGPnqRzmh0k7yj-nF2pJ8x95bYZlom9urtQuoT9zmKg92dgcIPTR_6ljH-LEotjYMNOWxQa-X-rtH0e-pjJS3UHxObYr9evI-zqQa1UqgNxFByh2V5DWhE2ZmJoEuMYfkWMvCRo8MKNtJt1yCz3XRQRtDF-5pWbWYlS6bbtZBvuqh-Ubd6zPrUAP6zWDOk8JLJLMMuDsgfsEfSOffXjidmHBy-OxsdSsB5N__PaO7-XjTHyws-c5bWHOfliHx7uo2CH6msO6mt-ZzSDd1BxJRyFoazMTBQ3zoJON24ZC7GgzQ3FWmEwL9ccWPoGNIy6B4nbNXGllTyFBlq7JDv4eHrmyj1d5NOw4GBCqaQm3854935Gx3DiNS8UlChaGnWvUxZrvrIUD5BDgU8VPHcGJE0IL1DF-Yua_Q_YflKTu1B3ib7oYcyGjJ3YL-HgpuKt79ay_1zUxKiaRxo_RqQRMlULHgIv_imnYvYYrQl2wwMBv0SpiwAC-PlwH4mG6gpbgJ3FayKbhAcz1iFvsSUOmcs8URA5Jcuvo7WV3gdkzm1TEVf0BbN7f4t9utL69gn23-r_jYkOnLV42-LkccqFlD4GFSUgmJqN1aHH3F-tB4g0rDBbmBSv1T5g60KVNFQ2MDzvxC5qH"}}
{"timestamp":"2025-09-22T13:30:37.494Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"rg --line-number \\\"AddConstraintViolationPenalties\\\" \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\"\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_U8nd8c5HWyVyXfZz31dV6dWZ"}}
{"timestamp":"2025-09-22T13:30:37.494Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_U8nd8c5HWyVyXfZz31dV6dWZ","output":"{\"output\":\"947:            AddConstraintViolationPenalties(objective, auxiliaryVars, context);\\r\\n995:        private void AddConstraintViolationPenalties(\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.2}}"}}
{"timestamp":"2025-09-22T13:30:37.494Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:30:40.735Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Reviewing AddFairnessRewards function**"}}
{"timestamp":"2025-09-22T13:30:41.098Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1087408,"cached_input_tokens":1047808,"output_tokens":4435,"reasoning_output_tokens":1792,"total_tokens":1091843},"last_token_usage":{"input_tokens":42240,"cached_input_tokens":42112,"output_tokens":71,"reasoning_output_tokens":0,"total_tokens":42311},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:30:41.099Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Reviewing AddFairnessRewards function**"}],"content":null,"encrypted_content":"gAAAAABo0U-ByWVwPkz_VwWtSGstf8ixXDB78qy8fOzFrcdUA43j0q5KtgCbvDrPY0KoTdjqDMxu29pxDOf1UXKaw-aKs_2P-oewsvkxDfNreobbd4uirfJuBImMqvta1XtbxAHU9n18yXlsCOHJWuAScPKaHbNk56RoyTjx8bGkL8kQMi8RwfGEviOus4DbaKy1gk-1DVN3__Np9h_tcr4y6WpoaSCyp1wa_3Yr7xGqDuK6SL9ziLb0zozwx5fHkaFAUdvQTWOqlfv9Slz10f0LL_8W38flDoaGsZk4XI16etGRXVVEaF8Gx7X_uUK3IKQC4NzVWDrdKkPfdsWB_ERLjxUEf6mNgseqdxMJFS3vjglMtjPeadLzexgcjHkS-tRsHAKVNaLPONSRWsOnagdqbOc75gHiwcMRd4crnS-w_4kJcie8m2SuJBUiz8RVJls_9O9swchsFi5W4wF38JegbGXzI_bTgrJ7PJoVMGMVVFOQ1rIoryNE4E1yBacpoUHjlq9airju6_wi_UnI6toDMHji5_lX92ePzpn_jxkjjJoTLkNRyYA8Y0IE9nmW4jsmX_cI9c4Ef9QKIu7Ho834oqtxJJL3jnLEnbXohZluS6dmw3RuCmDubb0YZqp25v4d364RuAKq2sDVW7zT175PCNdVZiXdP_1xyn_rINxqxDjCBg-fy4BnBRbkd3-rPSPGxBRYomk10Gp6cFCwiqqTo0fesa6hJxMaMR3y4_iATiMD7zeoi_NLUY8hTI-XGaC6MFItdsvFiFxczxEWjEUUwogcs4e4biKMreJRLL3ws9aSQhSloOXyKsztc72_OCxVQay_7ZCvKMmSuZ7naixRnx2RMMFRIt1MhIbu8H1ohPFydmRFxf3g0xov8V6gHs4NsNBxUROY"}}
{"timestamp":"2025-09-22T13:30:41.099Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"rg --line-number \\\"AddFairnessRewards\\\" \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\"\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_PeCujcfERiHe5UWWDLkpWSpz"}}
{"timestamp":"2025-09-22T13:30:41.099Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_PeCujcfERiHe5UWWDLkpWSpz","output":"{\"output\":\"950:            AddFairnessRewards(objective, auxiliaryVars, context);\\r\\n1022:        private void AddFairnessRewards(\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.2}}"}}
{"timestamp":"2025-09-22T13:30:41.099Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:30:42.929Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Checking specific code line**"}}
{"timestamp":"2025-09-22T13:30:43.956Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1129786,"cached_input_tokens":1090048,"output_tokens":4506,"reasoning_output_tokens":1792,"total_tokens":1134292},"last_token_usage":{"input_tokens":42378,"cached_input_tokens":42240,"output_tokens":71,"reasoning_output_tokens":0,"total_tokens":42449},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:30:43.956Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Checking specific code line**"}],"content":null,"encrypted_content":"gAAAAABo0U-E6Q_nnnqR4-MPkSmG0N1pplaRMl99lLefxlJcGRhCqOvFMhJsKvv3-z6BOrV0yol4xO2haG4Lbd1lnZXBLzpt9pMP7B-bni-qeiF2fZ4NRNNIXSPhhh5mAWxcZc3Bf6tj6MdIf-DVmMsPmWsCWAf6--d5Uw2LsuzkZdeAaqaLB7Mh8ffge9ky_GzvJdWV2me7sxCl9QFfEYyuvZlwQcijnrwGeJnj4Ag1TCyV-dSjpsvkupYmFJij8Gk8yVP7Y66srRt23kTsw4Vw5Ugj8ClxWd-uqqJTguRB_QGF707rzTEQzTZQqD9ySH65hIcafpXsZseyP2BlEiuG9WIbp8KhgwLKdoTzy0MGe7aH5ZTaaW2i7RRke6ATHX7-ZDHPHOlmikcelhsqS3LLNA4u9cxpflZ1LGY0LwAFnCowThwJI3q67u_ZIsfYMpyAV1b0LKsrlZys6qksKdmzskpobxU0vLNJrCyROuGHDRxr_pa2JkHcWyjVzOCHduDUWZx6o0IGVQhEMdOG3dCRSXEs4UUEL9afvKCWbF9RoLOGtMhmYLz6nrgJNgWAyTl4eBXkz-EzNN3snOqtRsgaAuuP5Fofy83pjgjgJPshkgICwkfii-RYwW1k-_2-eFgGt-zc1M8dTeoaupEKUNwfaJhkJlmcAfsOkQc9DkegFaMi8AJKBql4NgsgAq2ozuMAPXGVUjLneL6eflY-ZVTLow3Qh07PB-5k0LDGVJLN3HzkZYurdH8KdIyl-ls3WFah7jnnfdKZASX8sjT_AffiR--UxDY-18fPuXjYYHhbVVl_ipBEMVulAw7VpTAQsfkj1y03u4UAP8dtO5fT3mSPt6VLhnvh_3VR8fmgjORDnlvB2K6a6owfGNtElMgV8CHLEuaA8pMoDb6JdhHkhwt-cPddZlll-A=="}}
{"timestamp":"2025-09-22T13:30:43.956Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"rg --line-number \\\"ProcessEnhancedSolverResult\\\" \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\"\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_nKQFfTWlIu6QDJyCdBduZhZY"}}
{"timestamp":"2025-09-22T13:30:43.956Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_nKQFfTWlIu6QDJyCdBduZhZY","output":"{\"output\":\"93:                var solution = await ProcessEnhancedSolverResult(solver, decisionVariables, auxiliaryVariables, \\r\\n1087:        private async Task<GlobalOptimizedSolution> ProcessEnhancedSolverResult(\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.2}}"}}
{"timestamp":"2025-09-22T13:30:43.956Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:30:45.784Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Examining ValidateSolutionQuality line**"}}
{"timestamp":"2025-09-22T13:30:46.794Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1172315,"cached_input_tokens":1132416,"output_tokens":4576,"reasoning_output_tokens":1792,"total_tokens":1176891},"last_token_usage":{"input_tokens":42529,"cached_input_tokens":42368,"output_tokens":70,"reasoning_output_tokens":0,"total_tokens":42599},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:30:46.794Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Examining ValidateSolutionQuality line**"}],"content":null,"encrypted_content":"gAAAAABo0U-GOty7m9XD_DOpdY2-jRFv_aN25WxWtOcer7xKfmpZ46r2hAr4A0rsC1hJUP7GI9jXFQLu0A3AVMpB0bWY88-3GVO5QKKPmPRr_ggc5gowItX19RK176hj979sj7PpuDSIE56_8BZDTv0Gsg0K8KspifHzsYU4YkWmqueJ-Qq9cWdcUbXZUIH3JnEzWSzX2hNyNx9FYo5ZCzrAEs7SUDJYGQKN7SY-Yq5bJ1Um4GEOjnUe4rx2GSqQJSAnnKmyGrRHWURmU5bYkTjm1KmYy33J2Q96iYVd1Xi9vomhJRgM_yKmR14a_XTx9qlFkfrhbxdoplwQH7-6zsHjUKKNhZYJdk-Q2X-ToOxDKwSPW4UVMGTKGpYSWG1VooC1-KJhPOnFLo2IRb17ZvDpPw4s5gfQfGnd191XjSPRPhQFOtv9rk6gL_ZjAOQb-voVcryaFjTNlWWg1Z2ZjlUj-gL2_wbfxglCugNDCkv-3NWQYTJXMGBCUAntD85JxNbcDkxhw5LKqc9mTnJPcfAAbMWnEk7yactnAKqLr_4TJVu97M2c2Us5bbuMBiU1ez1YbbygcnBdXDhjXmTLLhALfqnlGEAaa-5w5rh40aKaioseXdsKyO72oAWoxwyyl-v4yF6SS0Zz5mWB4xgU2ohdF6KnuteV5Gtj0n8etf5mvjS42mCBLAZmYNKxHxc4krzrjuKOVXRn8WdVkxg9p8Hf7DmOBqiuY_ACGxGsza3_e2EA6Sg58IcfORaPJMLiJDA1Jq43ae26yNHd4yyl-ct_PlfUCjeAEaNhstL1ZmirEBl9RgnpnxvieKVoR1shw7AuwGiOZrxsNI2W21_KJaqMpO5gxTtY5kMLFMVf4aI0q2diE3gx7flaMDjf2EycihBqSsFx7EWoaC3Xy7zK7vqHucmcyaOo2A=="}}
{"timestamp":"2025-09-22T13:30:46.794Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"rg --line-number \\\"ValidateSolutionQuality\\\" \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\"\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_e5HadwM64aqsjZiXInHLL816"}}
{"timestamp":"2025-09-22T13:30:46.794Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_e5HadwM64aqsjZiXInHLL816","output":"{\"output\":\"1127:                var qualityMetrics = await ValidateSolutionQuality(assignments, auxiliaryVars, context);\\r\\n1156:        private async Task<SolutionQualityMetrics> ValidateSolutionQuality(\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.2}}"}}
{"timestamp":"2025-09-22T13:30:46.795Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:30:48.877Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Noticing class name reference**"}}
{"timestamp":"2025-09-22T13:30:49.712Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1214990,"cached_input_tokens":1174912,"output_tokens":4647,"reasoning_output_tokens":1792,"total_tokens":1219637},"last_token_usage":{"input_tokens":42675,"cached_input_tokens":42496,"output_tokens":71,"reasoning_output_tokens":0,"total_tokens":42746},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:30:49.713Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Noticing class name reference**"}],"content":null,"encrypted_content":"gAAAAABo0U-J63KkLA4uB3J4WzTYCQLBHnUx2p5HSiMXNmO5ykOxmShT5kkMGQJhPM5rKMhhjvKph3iLvBrEVxj2hx0oHp_0sfyzic3hQoH2S4hC_W5_ZaL8FjQPAF_6NqqiXuocSwxYRDLiXm8AioFwWrXT6OjI6nDQv9x2IVILBHPeIHX5Smzr6PG3ivsaERbhU1iDU3D529reHlxnsTgs4n7EAmyngPSQ3iaGlVrajIyJOuQMavnRWreG82Z4WhAonHkQ-UqK22UMTKelzYo0MESqZh7jYveQKfWTc8ia9Y6_ob6fv6t_X04xdhwr-9RwSeEA5ik9qr0RJuHIPnHTgmFEOCE2ZcIZqQpDXO5jSUnqTAAVLEo0KuZFbnrQmmy3BNyyh78QTd_O1cgFEOoeN5jkB-NVERUV2yhqT3CyeZNivj0DHnVNQE_QUs-1_cOWabVoVzTd1olLz2v1iQ9I3-V92tai8R8i19qqYg_b_CFTtMCuIENXekybKqmjjGiLODB9dMg-tNGnByhA3C9pJ8MZy68MF9TH_MKhBNM0cWOmHJrJ6CcRTLMkIFVAYzqYDi_gHjd_mqrdCOryfEmQMetnCEJ4PJdzLASKG6fHh6m3MhrK-hDYqsWWs88ATfWBJDBMWJmtSmLX49sXo75g9q6-9i6eNvmk6d_gly_4VQONjT6NNYPvqFR4HTfMK7XDpJuw_bPRmR6MCaMKpHz3Bs7-vIfYjcKfl47ykX-OdLfXNP8-AyuoU8KnGS_9wo-IxzFtIoGoAlwkaukSVrl9AExjUYdPoRdxvKbeSWdRHkxzjA2NH8SZSC1_SaYpZV3sP7D4rFO1igGT3_ZFOU3rhFryRXiiyYeCPIubOV0ixfn_wI77-QI5ECll7n6cs2HHRhnntcgM"}}
{"timestamp":"2025-09-22T13:30:49.713Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"rg --line-number \\\"LogWorkloadAnalysis\\\" \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\"\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_q7B5RloP4lAwjWlwlcbmOfdd"}}
{"timestamp":"2025-09-22T13:30:49.713Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_q7B5RloP4lAwjWlwlcbmOfdd","output":"{\"output\":\"1139:                LogWorkloadAnalysis(workloadDistribution, context.Tasks.Count, context.AvailablePersonnel.Count);\\r\\n1219:        private void LogWorkloadAnalysis(Dictionary<long, decimal> workloadDistribution, int totalTasks, int totalPersonnel)\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.2}}"}}
{"timestamp":"2025-09-22T13:30:49.713Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:30:51.778Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Checking BuildValidationContext reference**"}}
{"timestamp":"2025-09-22T13:30:52.682Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1257823,"cached_input_tokens":1217536,"output_tokens":4717,"reasoning_output_tokens":1792,"total_tokens":1262540},"last_token_usage":{"input_tokens":42833,"cached_input_tokens":42624,"output_tokens":70,"reasoning_output_tokens":0,"total_tokens":42903},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:30:52.682Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Checking BuildValidationContext reference**"}],"content":null,"encrypted_content":"gAAAAABo0U-M9uEGw9ZspgZTaDWBWPnoztgaLsh7DXyywJGd85njKZ_7dHkHJp_8sv58VmnnCMycyXy5SlQ4WhfvxXKMvbnEoa3LExc0DbEsSRP5Q-I1NWlsSMV83lWJB1FmDA7zH3vPIJFMBzzDIbhRZ_35GQI-DdumT61v_7I8XNGq2-MIu8-7p1BENUyMFFvTWN93yFUYOuDYkWhzXI9xSCfbkfb8iBkQXIDD0TTxJfkq_o8D1BqXHaQ4k7Y8YyeGKP-kLj16MVGQDW6J0V9GTT5tDoxCfnq7pKRvj96TjsgbHil_gSMANXFv7-gEGzWIVK5cTWyoGEoEJ5vqj0kZpb70eR-Y9okH-GGrmcKpE_rAtyrf0jbgFoiCEbWQZNY3MzXYIoiUOHgrQsCRjyp3l_KoXBm8Cn5KbbQL8AZXfxbTpdu-p32a0s6zQKlwYPOBGnlQQ8L90LTjAI81LI0wkkxMHFzoWtI5bvQembUqgO_WOij5PcZMli-DuuV7YJiSwSXPp8L7Pmn8InVY7SAFPNC8HfNZWELGJpIXu1BB9U65jM0gt58ir1jTP4CsBRhJJMxkusYsZ_Y2gAytE4h1IjYbYTEn19hu6haiRImtJIto676V004P5XYKaZHKjZrGAjrmOku4UfliP7eVZOfFtf5JGElJvWRA6WX-dCvUKhcNx_6J4Nc9giwqNrThvMnr9OSF-pbkMID-7ntsznlm4sc5yiWqU976INwKmciEHZ3IHXchbPblBEftjiVEWp_4zBt4nbhZCjgOpCCLnKXyvCfcfU2MXG4pTliiHlF68EIXQyYkWWjXcPlu6kVvvkW4XnQ4bDMzf4NRp7O6qikKExIy73bCjL58jdhiFokmwqYi1VQPEmEO7zXEkdXicv0ul734arTS"}}
{"timestamp":"2025-09-22T13:30:52.682Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"rg --line-number \\\"BuildValidationContext\\\" \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\"\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_MauOIwHUFNpX7ZxBd9nUMX9e"}}
{"timestamp":"2025-09-22T13:30:52.682Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_MauOIwHUFNpX7ZxBd9nUMX9e","output":"{\"output\":\"471:                        var otherAssignments = BuildValidationContext(personnelId, taskId, context, decisionVars);\\r\\n1249:        private List<WorkOrderEntity> BuildValidationContext(\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.2}}"}}
{"timestamp":"2025-09-22T13:30:52.682Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:31:21.938Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Outlining engine structure and features**"}}
{"timestamp":"2025-09-22T13:31:23.332Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1300803,"cached_input_tokens":1260288,"output_tokens":5875,"reasoning_output_tokens":2880,"total_tokens":1306678},"last_token_usage":{"input_tokens":42980,"cached_input_tokens":42752,"output_tokens":1158,"reasoning_output_tokens":1088,"total_tokens":44138},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:31:23.333Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Outlining engine structure and features**"}],"content":null,"encrypted_content":"[encoded data, 7544 characters]"}}
{"timestamp":"2025-09-22T13:31:23.333Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"rg --line-number \\\"CreateAdvancedSolver\\\" \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\"\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_0Tz2rV6QGgGAXhtmVLLPOnRx"}}
{"timestamp":"2025-09-22T13:31:23.333Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_0Tz2rV6QGgGAXhtmVLLPOnRx","output":"{\"output\":\"61:                using var solver = CreateAdvancedSolver();\\r\\n112:        private Solver CreateAdvancedSolver()\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.2}}"}}
{"timestamp":"2025-09-22T13:31:23.333Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:31:43.676Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Summarizing key code sections and pointers**\n\nI'll organize a detailed outline with bullet points referencing important methods and line numbers, covering the engine workflow, variables and constraints, objective functions and scoring, plus functionality gaps and potential improvements based on the code structure and comments. This structure should help clarify how the pieces fit together and where inactive or commented-out parts lie."}}
{"timestamp":"2025-09-22T13:31:44.549Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1344993,"cached_input_tokens":1304320,"output_tokens":6841,"reasoning_output_tokens":3776,"total_tokens":1351834},"last_token_usage":{"input_tokens":44190,"cached_input_tokens":44032,"output_tokens":966,"reasoning_output_tokens":896,"total_tokens":45156},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:31:44.549Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Summarizing key code sections and pointers**\n\nI'll organize a detailed outline with bullet points referencing important methods and line numbers, covering the engine workflow, variables and constraints, objective functions and scoring, plus functionality gaps and potential improvements based on the code structure and comments. This structure should help clarify how the pieces fit together and where inactive or commented-out parts lie."}],"content":null,"encrypted_content":"[encoded data, 6412 characters]"}}
{"timestamp":"2025-09-22T13:31:44.550Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"rg --line-number \\\"CalculateQualificationScore\\\" \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\"\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_Vcq2YuEBAVbLBTxZ18XSeJZV"}}
{"timestamp":"2025-09-22T13:31:44.550Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_Vcq2YuEBAVbLBTxZ18XSeJZV","output":"{\"output\":\"1374:                var qualificationScore = CalculateQualificationScore(personnelId);\\r\\n1412:        private double CalculateQualificationScore(long personnelId)\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.2}}"}}
{"timestamp":"2025-09-22T13:31:44.550Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:31:47.573Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Locating CalculateExperienceScore function**"}}
{"timestamp":"2025-09-22T13:31:48.500Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1390247,"cached_input_tokens":1349376,"output_tokens":6911,"reasoning_output_tokens":3776,"total_tokens":1397158},"last_token_usage":{"input_tokens":45254,"cached_input_tokens":45056,"output_tokens":70,"reasoning_output_tokens":0,"total_tokens":45324},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:31:48.500Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Locating CalculateExperienceScore function**"}],"content":null,"encrypted_content":"gAAAAABo0U_En26d_ZIh-tJqgKaAiKEr4WXLPf-Gr-3KpXNo2Q0Xe0yrvX5qYAm5EuCnO-S2QBY1PiOS2FK5kTGUnMwQtmcDYs9gnUihuHbwIKSnSI9iQdfOyc4yvF6ESgP9KKIdttzLACRe8F0FIuPYCdsl8l4Vdmwdq9D2-hwi7vrxgE3MiRi-USB99o6pSR48w8bGY6TKHDGVH6-LpfCfV9oP_gzX5EPLE-4PPssWoFqmPtyd96S_js3URHSLRHwTI7Peu_Pj9mfbw9t3SBaQJi33E1hlF8ddhE718UwhxivBiZcvuYDqge8bVBGeBwG0xLOF8MVGgCsDg2tUxm_0LOGe4poKTWZH2q9E-Ee_ZFuCGRFRuwCwQ_uhal045ihfRkZM__RPX6dQSb1vdNcA6pyp2W7-q759aamUpN--yVlOkZj0URIywaiZ1jLscz7s6CnOmcl8nV-PCJZGDrmKIkjrVXdlX8gESx-TWIobvUW4lWOp1qa7rI-XcYPaKz0l85KCn5qY8Vn4CPoFmlHU_FWyiJiibd1kt2eD0fsy4NIchgo9HL4Xfy_EKB20vbAKhs95gtBpq9VQ8Kwn2VC-IffPPmIjn3ahaTa_nGS1fz4jGpzXahJKR3Gyy1mNmZezBf2CIYoGalcu6O4E1syLPgyboVGV-__X_6DeZLFbi_3yvANXubc_56J_8w4490kyrkWU3eQJmv1U9X4mEf-PKELLDUiGMElsRXMLw8-unr9DXHrd1F0YpWa6KgZ4srVOV57UZjGl-UdfKVciAOPfK9WEgXbZ14naR6UJ5RTRBkyKzt_xGlo8v2jhKdZVhx7K1xsWqA0PLYwH80iMScVe0xlzX1vyr8Y9WoIQT0vqg3dVGtJtjjOHl-eSDArhUXNsEq82vcNKmYLcaVVq7se5c3WcoZx1Hw=="}}
{"timestamp":"2025-09-22T13:31:48.500Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"rg --line-number \\\"CalculateExperienceScore\\\" \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\"\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_RRmIaH2an6qRKVir4czkqy2Z"}}
{"timestamp":"2025-09-22T13:31:48.500Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_RRmIaH2an6qRKVir4czkqy2Z","output":"{\"output\":\"1377:                var experienceScore = CalculateExperienceScore(personnelId);\\r\\n1456:        private double CalculateExperienceScore(long personnelId)\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.2}}"}}
{"timestamp":"2025-09-22T13:31:48.500Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:31:50.712Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Checking CalculateSeniorityScore line**"}}
{"timestamp":"2025-09-22T13:31:51.553Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1435639,"cached_input_tokens":1394560,"output_tokens":6982,"reasoning_output_tokens":3776,"total_tokens":1442621},"last_token_usage":{"input_tokens":45392,"cached_input_tokens":45184,"output_tokens":71,"reasoning_output_tokens":0,"total_tokens":45463},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:31:51.553Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Checking CalculateSeniorityScore line**"}],"content":null,"encrypted_content":"gAAAAABo0U_HVxE3dGzmti9IqWzYVDizm4-caq4wC_W91TfenEv4358JBq3-5MsB4W2TrjmPxzQvNAoOIYGYVTLh1KqE6GLw3CrODv9B97KjOPmuA-BkdRsmXofUvbWA_5L-BJCdb4zEib_JJkk7Yqn3zV-0rYZzv67WA6Ph54cpM0ngWWN96evArr4pcBymNXh3NLaV-TBgEFEsFwBUKECn_j1KlpPoeiTNttBh9pD3B743ArlRw1m8v9NbfXDbVhAHQockGRxz7qJy8AQuFjcDQa7ABUGLn_d8n7cGJSkPjSh3ZM_FUp-IjAT28evKomRwcV2XuSbuO6P6NYgY4a5TmXdRtgbxllsia8fNngeM4I3HXff-DJ-u1ioz39qdUhzXjWKUZYRxUeqPDwkKCZCNjE7cTaG4gbb7995laV4TG3Kp1Nku7v5vbnVXdfN1OLxYMe5fcCVWLsXw2OFzK1W17Ote7C37CVq1vDz8UDMmI0wOUejngF_phqA35S76mEvjPpCGqw6qFpB5Rvd5nES-js86-sKC-SAetOMmJiLrSdaEBVGPYtI-unxN0LIwXFSAh0OyEaqoyl8Erv1Q90zL3iXkmN7GcoydmCFUF9YG8Q5coW89Rd1dm5Wh8KUZnqgVCd_CKLkt3eJIOfxz3qKIHjBByzV60BIzwWv7kGkizDUsdBE-n_pqYJUKU8Z_7NL-7-df_lC3tZyuAoOJr1YjFed7XnhhB9YGkg1eB56ULl5svthGVTk0UpGB-9YniyI3HG_AhB5zUUhpe3KUkz_V8H9vgkCLKAV9f_S6bRVrUwr5mfGsmu83OIIY-Q14HqmUTkPAtptOe_J9_Z-z4LKEAaU-CpLOwKKv3-Xr_4NjD8h2OEh2BQcAAjQ5yrYtpMHFlZesiHGV00PkYyZn-tXZEzCkhzFkRA=="}}
{"timestamp":"2025-09-22T13:31:51.553Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"rg --line-number \\\"CalculateSeniorityScore\\\" \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\"\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_7yxJAOCAXbVufY07GQF48D1Y"}}
{"timestamp":"2025-09-22T13:31:51.553Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_7yxJAOCAXbVufY07GQF48D1Y","output":"{\"output\":\"1380:                var seniorityScore = CalculateSeniorityScore(personnelId);\\r\\n1497:        private double CalculateSeniorityScore(long personnelId)\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.2}}"}}
{"timestamp":"2025-09-22T13:31:51.553Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:31:55.285Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Noting method usage and validations**"}}
{"timestamp":"2025-09-22T13:31:56.278Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1481174,"cached_input_tokens":1439872,"output_tokens":7117,"reasoning_output_tokens":3840,"total_tokens":1488291},"last_token_usage":{"input_tokens":45535,"cached_input_tokens":45312,"output_tokens":135,"reasoning_output_tokens":64,"total_tokens":45670},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:31:56.278Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Noting method usage and validations**"}],"content":null,"encrypted_content":"gAAAAABo0U_MHp4kb6oPGOGxD_G7FlxilMpU18ug6LIazUEdA5d2PACP69qO3hWgF5ZZkTbeq83eC5PPpY29yJz-SyADNry2ySU3FXQc9OPCj1Y18gsiR2wNtectUs3m-XEUnmDPDlCN9umnYk2J2EYf_aHo4jMcZX1V9rV76a0wAdpDcolWC7dIoCyuP4x4M0QW2jRu1kMP8cQsBrCmmGU5iV_sHWgfNpQrYrq_SJu2JqOQIfY30BwRw6KNrKk-_bOWkut3ctcodoQGRxxhKlCm2WECufmz14ZTTIZt-aeP7XJ_4JkkInMkwJS1JW_esWHuAkvQAXXoNfzI6xFR5hyI53IbRpC67h437FTjRkQ8zVl7rCPCs-imYUSPw1gac65ShD9XfLSIWK9rCuRIpQmnycUFiF1a412AV7Hruf2F88BxHvffI7RyG82Pip-LVGkOzm_YZra8YH7FigQy_yNVNbddSuJoCABT-tMXUFBzgTieR9W92ZkZHxw9TfDyZ4DAyWWpM31OJuxsRdgws3pPZqjQWZHcqbLZU8qtEkwjxo5c_sBx-MUhso8Y3jiHHGw0_GaNqfAkFoAj8ZNbI9nm1KlzK2UT_05FfK_Wl-QLVeLYlbQTMCIzKnpVTQDT_gsR2kdmybQnZyZCoIzetnXpxxwdVze3gfXEAUYtVdf05vj-YUkJCdiS0iZQQ5mIr70uUYYlurr2eJbtFhAzbzOfHLnclZHbOdcXjwS-_PiO3bXwQjmsre9t_9FgFqic_MdAPzyLL3kScmef-mw7M-2YODNdw6mRJHEr26cbdZYXqkZF2Io-xkBBT6pg6pf2gyqTJj6XLJTJ-HCXe2kjYUIwoZTOTPICF-NEuipOUVw9Smz8Mo2P0CQrPX7Afuq-iP0-zCzWMG8jVwuvsNwNVX8TWODEKpLe3FQN8MEJQJ_IiOyxeWO3ewZG3AzMHZaLdFNiTDAE0KwmJutZ2Uojc5kIeLFIlnzx55v80vMCe_GkdUOpjkDkB3pdpurGZcLmmo2o-h8bJNQrRiBOS23fNhdM_jnto8C7AKT6lSJ9gjzd4L9sUP9TSvGu_5-D31wp9p7s-ZT-6XyvqpH_2a2pGfvBzrHKdfe_G8c3mjpAjpUkrhI4-jlvz4VmBu1oqhP1Q3XyNpuvf6T-g3CrfprEOXF9C9mkHgnd_4CbbEJD4_D3Q5Xae1whxcrtI6LjtMLQfmNfWD2t9HM7mLn0ds5G9W-8y1f404XIXeckYHVFa9JXR5jy0KlWBEAUigp3NBt62Ug9A1NB4Xvv2EaaefAKayaKaCPPAaUuVbIJPxgojyjeBLUGwJaE_CAoq3vx0Thafme00_hIiQ22eaQwMun7tSO6dhyqXb_8T3zAGzDeEtQRAXpj8VOeZQTI9wf1vYrtaUNS5LBZxI62"}}
{"timestamp":"2025-09-22T13:31:56.278Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"rg --line-number \\\"CalculateSkillMatchingBonus\\\" \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\"\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_Hvp4L3MwoYlND2TGH9u1uRHm"}}
{"timestamp":"2025-09-22T13:31:56.279Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_Hvp4L3MwoYlND2TGH9u1uRHm","output":"{\"output\":\"984:                    var skillBonus = CalculateSkillMatchingBonus(task, personnelId, context);\\r\\n1649:        private double CalculateSkillMatchingBonus(WorkOrderEntity task, long personnelId, GlobalAllocationContext context)\\r\\n1685:                baseScore += CalculateSkillMatchingBonus(task, personnelId, context);\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.2}}"}}
{"timestamp":"2025-09-22T13:31:56.279Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:32:43.186Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**整理功能分析总结**\n\nI'll organize the key findings into four sections with 4-6 bullets each, carefully referencing relevant method names and line numbers. Starting with engine flow and solver orchestration, then variables and current constraints, followed by objective and scoring components highlighting commented-out rewards, and finally gaps and risks emphasizing unreachable advanced validations and heuristic risks. The goal is a clear, friendly Chinese summary with accurate line references and balanced bullet counts."}}
{"timestamp":"2025-09-22T13:33:06.041Z","type":"event_msg","payload":{"type":"agent_message","message":"**引擎流程**\n- `OptimizeAsync` 串联“建模 → 三层约束 → 公平性 → 目标函数 → 求解 → 结果解析”，并在异常时返回保底空方案保障调用方稳定性 (NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs:51).\n- `CreateAdvancedSolver` 使用 OR-Tools CBC MIP，启用割平面、启发式、预处理与多线程配置，目标是支撑大规模约束 (NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs:112).\n- `ProcessEnhancedSolverResult` 将求解结果转换为任务→人员映射，累计评分并构建工作量分布，同时记录解的目标值与约束满足度 (NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs:1087).\n- `ValidateSolutionQuality`/`LogWorkloadAnalysis` 计算任务完成率、时间冲突率、负载均衡度与利用率等指标，为后续监控和调优提供数据 (NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs:1156,1219).\n\n**变量与当下约束**\n- `BuildDecisionVariables` 仅为通过班次可用性+预筛选阈值的任务/人员组合建 Bool 变量，先期裁剪搜索空间 (NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs:141).\n- `BuildAuxiliaryVariables` 构建工作负载、正/负偏差与时间冲突指示变量，为公平性与惩罚建模提供支撑 (NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs:205).\n- Level 1 约束确保每个任务恰好分配一人、同岗位同日不重叠，并将任务计数与工作量变量绑定，形成基本可行域 (NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs:278).\n- `AddFairnessConstraints` 通过负载平衡方程、最大负载上限和最少参与人数来抑制资源集中，额外创建参战指示量 (NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs:835).\n\n**目标与评分**\n- `SetEnhancedObjectiveFunction` 汇总基础匹配分、约束惩罚、公平性奖励、业务奖励等组件，并以最大化方式求解 (NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs:932).\n- `AddBaseAssignmentScore` 根据预筛选评分放大贡献，并叠加技能匹配奖励，将先验评估直接转化为目标系数 (NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs:961,984,1649).\n- `AddConstraintViolationPenalties` 当前仅对时间冲突指示量施加百万级惩罚，其余 Level2/Level3 惩罚循环被注释导致未生效 (NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs:995).\n- `AddFairnessRewards` 与 `AddBusinessPriorityRewards` 被定义但调用/系数设置被注释，因此公平性奖惩与业务优先级在目标函数中处于关闭状态 (NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs:950,1022,1048).\n\n**功能空洞与风险**\n- Level 2/Level 3 约束的核心调用被注释，批次班次规则、FL 优先、技能/连续性/资质等业务约束未进入模型，实际仅依赖 Level 1 + 公平性约束 (NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs:393,588).\n- 虽实现了批次感知班次校验、全局时间窗和批次完整性等大量辅助逻辑，但因入口被注释这些约束、违规变量与矩阵构建均未影响求解结果 (NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs:407,1769,2060).\n- `AddPersonnelUnavailabilityConstraints` 仍未被调用，硬约束只依赖变量构建阶段的过滤；一旦后续逻辑重新引入不可用组合，模型缺乏兜底限制 (NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs:600,2192).\n- 资质/经验/资历评分以人员 ID 取模模拟，缺乏真实数据驱动，若这些值被用于目标或约束，易造成偏差 (NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs:1412,1456,1497)."}}
{"timestamp":"2025-09-22T13:33:06.106Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1526960,"cached_input_tokens":1485440,"output_tokens":10262,"reasoning_output_tokens":5888,"total_tokens":1537222},"last_token_usage":{"input_tokens":45786,"cached_input_tokens":45568,"output_tokens":3145,"reasoning_output_tokens":2048,"total_tokens":48931},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:33:06.106Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**整理功能分析总结**\n\nI'll organize the key findings into four sections with 4-6 bullets each, carefully referencing relevant method names and line numbers. Starting with engine flow and solver orchestration, then variables and current constraints, followed by objective and scoring components highlighting commented-out rewards, and finally gaps and risks emphasizing unreachable advanced validations and heuristic risks. The goal is a clear, friendly Chinese summary with accurate line references and balanced bullet counts."}],"content":null,"encrypted_content":"[encoded data, 13796 characters]"}}
{"timestamp":"2025-09-22T13:33:06.106Z","type":"response_item","payload":{"type":"message","role":"assistant","content":[{"type":"output_text","text":"**引擎流程**\n- `OptimizeAsync` 串联“建模 → 三层约束 → 公平性 → 目标函数 → 求解 → 结果解析”，并在异常时返回保底空方案保障调用方稳定性 (NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs:51).\n- `CreateAdvancedSolver` 使用 OR-Tools CBC MIP，启用割平面、启发式、预处理与多线程配置，目标是支撑大规模约束 (NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs:112).\n- `ProcessEnhancedSolverResult` 将求解结果转换为任务→人员映射，累计评分并构建工作量分布，同时记录解的目标值与约束满足度 (NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs:1087).\n- `ValidateSolutionQuality`/`LogWorkloadAnalysis` 计算任务完成率、时间冲突率、负载均衡度与利用率等指标，为后续监控和调优提供数据 (NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs:1156,1219).\n\n**变量与当下约束**\n- `BuildDecisionVariables` 仅为通过班次可用性+预筛选阈值的任务/人员组合建 Bool 变量，先期裁剪搜索空间 (NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs:141).\n- `BuildAuxiliaryVariables` 构建工作负载、正/负偏差与时间冲突指示变量，为公平性与惩罚建模提供支撑 (NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs:205).\n- Level 1 约束确保每个任务恰好分配一人、同岗位同日不重叠，并将任务计数与工作量变量绑定，形成基本可行域 (NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs:278).\n- `AddFairnessConstraints` 通过负载平衡方程、最大负载上限和最少参与人数来抑制资源集中，额外创建参战指示量 (NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs:835).\n\n**目标与评分**\n- `SetEnhancedObjectiveFunction` 汇总基础匹配分、约束惩罚、公平性奖励、业务奖励等组件，并以最大化方式求解 (NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs:932).\n- `AddBaseAssignmentScore` 根据预筛选评分放大贡献，并叠加技能匹配奖励，将先验评估直接转化为目标系数 (NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs:961,984,1649).\n- `AddConstraintViolationPenalties` 当前仅对时间冲突指示量施加百万级惩罚，其余 Level2/Level3 惩罚循环被注释导致未生效 (NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs:995).\n- `AddFairnessRewards` 与 `AddBusinessPriorityRewards` 被定义但调用/系数设置被注释，因此公平性奖惩与业务优先级在目标函数中处于关闭状态 (NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs:950,1022,1048).\n\n**功能空洞与风险**\n- Level 2/Level 3 约束的核心调用被注释，批次班次规则、FL 优先、技能/连续性/资质等业务约束未进入模型，实际仅依赖 Level 1 + 公平性约束 (NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs:393,588).\n- 虽实现了批次感知班次校验、全局时间窗和批次完整性等大量辅助逻辑，但因入口被注释这些约束、违规变量与矩阵构建均未影响求解结果 (NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs:407,1769,2060).\n- `AddPersonnelUnavailabilityConstraints` 仍未被调用，硬约束只依赖变量构建阶段的过滤；一旦后续逻辑重新引入不可用组合，模型缺乏兜底限制 (NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs:600,2192).\n- 资质/经验/资历评分以人员 ID 取模模拟，缺乏真实数据驱动，若这些值被用于目标或约束，易造成偏差 (NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs:1412,1456,1497)."}]}}
{"timestamp":"2025-09-22T13:33:55.039Z","type":"response_item","payload":{"type":"message","role":"user","content":[{"type":"input_text","text":"# Context from my IDE setup:\n\n## Active file: NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\n\n## Active selection of the file:\nCreateAdvancedSolver\n## Open tabs:\n- LinearProgrammingEngine.cs: NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\n\n## My request for Codex:\n分析CreateAdvancedSolver存在什么问题，帮我优化下\n"}]}}
{"timestamp":"2025-09-22T13:33:55.039Z","type":"event_msg","payload":{"type":"user_message","message":"# Context from my IDE setup:\n\n## Active file: NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\n\n## Active selection of the file:\nCreateAdvancedSolver\n## Open tabs:\n- LinearProgrammingEngine.cs: NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\n\n## My request for Codex:\n分析CreateAdvancedSolver存在什么问题，帮我优化下\n","kind":"plain"}}
{"timestamp":"2025-09-22T13:33:55.039Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:34:43.144Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Evaluating CreateAdvancedSolver method**"}}
{"timestamp":"2025-09-22T13:34:45.472Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1569306,"cached_input_tokens":1487872,"output_tokens":11958,"reasoning_output_tokens":7488,"total_tokens":1581264},"last_token_usage":{"input_tokens":42346,"cached_input_tokens":2432,"output_tokens":1696,"reasoning_output_tokens":1600,"total_tokens":44042},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:34:45.472Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Evaluating CreateAdvancedSolver method**"}],"content":null,"encrypted_content":"[encoded data, 10572 characters]"}}
{"timestamp":"2025-09-22T13:34:45.472Z","type":"response_item","payload":{"type":"function_call","name":"update_plan","arguments":"{\"explanation\":\"准备优化 CreateAdvancedSolver：梳理现状、改造配置、验证输出。\",\"plan\":[{\"status\":\"in_progress\",\"step\":\"梳理 CreateAdvancedSolver 当前问题与约束配置风险\"},{\"status\":\"pending\",\"step\":\"实施改造：加强参数配置与健壮性处理\"},{\"status\":\"pending\",\"step\":\"检查代码并总结调整影响\"}]}","call_id":"call_IUMTBc7OyxJh0FGjD2UVv7xt"}}
{"timestamp":"2025-09-22T13:34:45.472Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_IUMTBc7OyxJh0FGjD2UVv7xt","output":"Plan updated"}}
{"timestamp":"2025-09-22T13:34:45.472Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:35:11.756Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Evaluating solver configuration changes**\n\nI'm carefully reviewing how to improve the solver setup by adjusting time limits, threading, and parameters like mip gap and tolerances, while checking API availability to avoid breaking changes and ensuring parameter strings are formatted correctly. I want to use constants properly and consider fallback behaviors if some methods aren't supported in the current environment."}}
{"timestamp":"2025-09-22T13:35:13.278Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1613417,"cached_input_tokens":1531776,"output_tokens":13223,"reasoning_output_tokens":8704,"total_tokens":1626640},"last_token_usage":{"input_tokens":44111,"cached_input_tokens":43904,"output_tokens":1265,"reasoning_output_tokens":1216,"total_tokens":45376},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:35:13.278Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Evaluating solver configuration changes**\n\nI'm carefully reviewing how to improve the solver setup by adjusting time limits, threading, and parameters like mip gap and tolerances, while checking API availability to avoid breaking changes and ensuring parameter strings are formatted correctly. I want to use constants properly and consider fallback behaviors if some methods aren't supported in the current environment."}],"content":null,"encrypted_content":"[encoded data, 7928 characters]"}}
{"timestamp":"2025-09-22T13:35:13.278Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"rg \\\"SetDoubleParam\\\" -n\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_MIf3jEx4UfNfU0O2k359qTl1"}}
{"timestamp":"2025-09-22T13:35:13.278Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_MIf3jEx4UfNfU0O2k359qTl1","output":"{\"output\":\"\",\"metadata\":{\"exit_code\":1,\"duration_seconds\":1.3}}"}}
{"timestamp":"2025-09-22T13:35:13.278Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:35:46.752Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Designing solver parameter configuration**"}}
{"timestamp":"2025-09-22T13:36:02.328Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1658862,"cached_input_tokens":1577088,"output_tokens":15200,"reasoning_output_tokens":9984,"total_tokens":1674062},"last_token_usage":{"input_tokens":45445,"cached_input_tokens":45312,"output_tokens":1977,"reasoning_output_tokens":1280,"total_tokens":47422},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:36:02.328Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Designing solver parameter configuration**"}],"content":null,"encrypted_content":"[encoded data, 7972 characters]"}}
{"timestamp":"2025-09-22T13:36:02.328Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"$patch = @'\\n*** Begin Patch\\n*** Update File: NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\n@@\\n-using System.Threading.Tasks;\\n+using System.Text;\\n+using System.Threading.Tasks;\\n@@\\n-        private Solver CreateAdvancedSolver()\\n-        {\\n-            var solver = Solver.CreateSolver(SOLVER_TYPE);\\n-            if (solver == null)\\n-            {\\n-                throw new InvalidOperationException(\\\"无法创建增强版线性规划求解器\\\");\\n-            }\\n-\\n-            // 高性能配置\\n-            solver.SetTimeLimit(MAX_SOLVER_TIME_SECONDS * 1000);\\n-            \\n-            // 设置优化参数\\n-            solver.SetSolverSpecificParametersAsString(\\n-                \\\"cuts=1 \\\" +           // 启用割平面\\n-                \\\"heuristics=1 \\\" +     // 启用启发式算法\\n-                \\\"presolve=1 \\\" +       // 启用预处理\\n-                \\\"threads=0\\\"           // 使用所有可用线程\\n-            );\\n-\\n-            _logger.LogInformation(\\\"🔧 高性能求解器创建完成，配置：时间限制{TimeLimit}s，多线程支持\\\", MAX_SOLVER_TIME_SECONDS);\\n-            return solver;\\n-        }\\n+        private Solver CreateAdvancedSolver()\\n+        {\\n+            var solver = Solver.CreateSolver(SOLVER_TYPE);\\n+            if (solver == null)\\n+            {\\n+                throw new InvalidOperationException(\\\"无法创建增强版线性规划求解器\\\");\\n+            }\\n+\\n+            var timeLimitMs = (long)MAX_SOLVER_TIME_SECONDS * 1000L;\\n+            solver.SetTimeLimit(timeLimitMs);\\n+\\n+            var suggestedThreadCount = Math.Max(1, Math.Min(Environment.ProcessorCount, 16));\\n+\\n+            var parameterBuilder = new StringBuilder()\\n+                .AppendLine(\\\"cuts=1\\\")\\n+                .AppendLine(\\\"heuristics=1\\\")\\n+                .AppendLine(\\\"presolve=1\\\")\\n+                .AppendLine($\\\"threads={suggestedThreadCount}\\\");\\n+\\n+            if (OPTIMALITY_TOLERANCE > 0)\\n+            {\\n+                parameterBuilder.AppendLine($\\\"ratioGap={OPTIMALITY_TOLERANCE}\\\");\\n+            }\\n+\\n+            solver.SetSolverSpecificParametersAsString(parameterBuilder.ToString());\\n+\\n+            _logger.LogInformation(\\n+                \\\"🔧 高性能求解器创建完成，配置：时间限制{TimeLimit}s，线程数{ThreadCount}，最优性容忍度{Tolerance}\\\",\\n+                MAX_SOLVER_TIME_SECONDS,\\n+                suggestedThreadCount,\\n+                OPTIMALITY_TOLERANCE);\\n+            return solver;\\n+        }\\n*** End Patch\\n'@; git apply -v $patch\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_FXc0GCnhxRj8NVfXTSXbeFuH"}}
{"timestamp":"2025-09-22T13:36:02.328Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_FXc0GCnhxRj8NVfXTSXbeFuH","output":"{\"output\":\"error: can't open patch '*** Begin Patch\\n*** Update File: NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\n@@\\n-using System.Threading.Tasks;\\n+using System.Text;\\n+using System.Threading.Tasks;\\n@@\\n-        private Solver CreateAdvancedSolver()\\n-        {\\n-            var solver = Solver.CreateSolver(SOLVER_TYPE);\\n-            if (solver == null)\\n-            {\\n-                throw new InvalidOperationException(无法创建增强版线性规划求解器);\\n-            }\\n-\\n-            // 高性能配置\\n-            solver.SetTimeLimit(MAX_SOLVER_TIME_SECONDS * 1000);\\n-            \\n-            // 设置优化参数\\n-            solver.SetSolverSpecificParametersAsString(\\n-                cuts=1': No such file or directory\\n\",\"metadata\":{\"exit_code\":1,\"duration_seconds\":0.2}}"}}
{"timestamp":"2025-09-22T13:36:02.328Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:36:15.630Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Diagnosing git apply patch issue**\n\nI'm figuring out why `git apply` fails with the patch string—realizing it treats the string as a file path instead of patch content. The core problem is that the patch content, including Chinese characters and quotes, isn’t properly passed; I need to pipe the patch text into `git apply -` to provide it via STDIN instead of as a filename argument."}}
{"timestamp":"2025-09-22T13:36:20.292Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1706504,"cached_input_tokens":1623808,"output_tokens":16283,"reasoning_output_tokens":10368,"total_tokens":1722787},"last_token_usage":{"input_tokens":47642,"cached_input_tokens":46720,"output_tokens":1083,"reasoning_output_tokens":384,"total_tokens":48725},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:36:20.292Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Diagnosing git apply patch issue**\n\nI'm figuring out why `git apply` fails with the patch string—realizing it treats the string as a file path instead of patch content. The core problem is that the patch content, including Chinese characters and quotes, isn’t properly passed; I need to pipe the patch text into `git apply -` to provide it via STDIN instead of as a filename argument."}],"content":null,"encrypted_content":"gAAAAABo0VDQewbDReNtOvY8yd9FYGc_vg3DzZIcw78eT_PAs0EidNVuAc3KnE7ylWY38kcKJKFA_RONHNpG-uqOhrBpsaOGojy_hEOOXfltX2BcQuTUgkkALBa6CwwuLS_6CRXoOPLs291VzQwVl_u3pyhfJWKLwC68SzIIpfiwuFR9AESY5xj3zsWlma4_1dxUI54WJ1kCobTk9hRPVtnqzHrTSRqlqW7Hf5x1wYXdS0_0VYxIRMBUsQ7Ir0yOmzsjsrPjevepr_brQpL473HdSAe4w0cvNtzNbPqEJsjFShVPrES0dIJcdPq7AiysQX5VJUPuUiu8DlSOylTOW-RdZtWK6f71yKf7mYewEp4fAedJ2dk7emyU5ovuDXQyZns3-Pog6pq9KsLAf0512g4H1IGltZLeXaW2i1OUsG4lQeDaPR4Z9OYadwlzvquuFhn9_0HjIQB8XCsQ3Gi9hgaAeG5VuHSg-g9Ea25WzgmFAwFt7nkENcHw0lmfQzh2o9qHhyoxaTZQsKEUrYDDkRcMyx9YU2QKhRa9w7fvI5oTAYEMqxNKzjijczb7OZatSVlrBUW86e11HIAjQlaPvLgkOEsyTsMcYJ8QR_QfRNaMgGA2g4ig50D7XY0dOikYOVpxldddKBupBZkHHYS5xe-lYdaNcdVdWz_0riEWQcIFptZs2vbFDyBFCkiRuAiGFX220XlB-FFz9Rw9fCxaFuo8vKXqxxwCSPtm2AkMzqJ_EtW3ViN9vCj2AkJKBPxwGt_3s7HvSXn7RghcNIMoIED1QaUEA7z-MwKcDbP_AsgpnNgwN3d1wnlqpPaCFp4eOQR0gWYEY26W1xETN0UJGzhnQbSV3fK2OyCc9vGKBg8tepnl2TaJMCOO2kFuhGZGC8b5c2lOcMdZg8W7oi1qiUdCUI62c6fej7-Ed6IMqKU_M83lpA1S0kHErb3cfm8EqBoZj3-liN8oYqk2b37R4pbyOFJO7VH9njgdkzATMX1IiFd7kapMNkPX4ugSY2unDHH5sABQiJ9R10tcbNFs7MENjzYOQBkSo8UURQG66l_7RzO8dkAPZ5tTuNXQ7pGKW8m0-H2fJ9ihnNAjerBlm1nAxaOtwS-RA9QpvkuG5yL9MHGI4WmcISINtz7mF33uy3j7EQsr9O6iWynZNQXqA7FeELZqOaTnNHiAeadprdf2P8gXAKjqCN7Oy2EIGMsEw6bhvDhqVWtjH0XR0VJdNZKhSIBUtB8IIklJAHpf0ywMXGS8WNTLtV4Bvdi1Y_XQ8vD7TILUh3W_F6kZVvtRhWVN9EpSGt93xgKYi60rNgsKZrKrZaFsaMIt8PY6zmrPEnTM5XE--ccaY_QZZgeaqwM0iQ4cpsl7jRFvVBj-rNYgTrvOcMXX83Z1McMWOnakeUnzw1X2GEZIqaNFebkCrmCiHCI9pdN97rsro9zrUXnWt2q1zjdtmWXH3fUq9nTbu_sLcRKHM00TRbdFOP-NZOGSlDwNgoZjhXhr0lBrNTGzAQlkbZOoQmPqX_cDC5_Szcg2VkV7UHNFsXcWPHNolO_64u4vvUP6gpsR8L4LKPt-t7a3x_QH8TkKUbZuSTyxV-GHbs2eYSSm82ShiNODdWbURM36AdwQXIOnreKaVpUipFmqIEJQY5qr54NTsHKPPucBegY6_oatUQZOndkJWZGZYw6SZ1CDTC3P-fJjYwnbKs0YIJwM6lgpkjC0POtsGUMmTh5c0mJr17vCxtXRdm0f52agjIhS3b-_gPjGDppOFsEY-ilM86eeJr5cb4aBE4rf5F5I_mLYPk2rfrmcGafKn2JxWXbU3cQdJTZk0GjrwbAIBTsymlsQoo-_kJCdgf83YdyKUni-nB1tcv2ZFk6CXvmkYjlTXB8sYExgVGWf3E6YzkDzWYk2SWoB7YBLziGwmOUuXgddMlomjbCtOCnHunKy7VhJvDBg80S7-HRfzabLl2A0nhXc_nFxIUkvl5aJcbYLeVDa3CVja_OcE_WRDGkFpsShV823wimEWiBC5g-TvIuR6ninIKa1oB0YaR5ePZdMPWPll5gU3G2JyorY0hvZKq0AB1n2GELuANd0vsBq0gtz_ue-tpCdUZTEF-e-U_lJcvGPzrMx8AyhSs-1xOHxU8VF6wRRY49jS4XgJnvzm-MRMDvDDhpfbEsTej59C0pQwH78fAyDh8F94lgGFixrjvCAwB-jq5ze3pteksUOmHWkBr9kRRlyz7rj9bymfLXo2KZl35Ygs-pourp5kzxY0d8x0JyHKhbPchohagYBJxVcI16F5_KojJXURb2p08FtnUrFkmsmIbVJONvR-9ATRQSLOPIHuY5l4E_uCY-HUKoRd_KZH5eIzyNKVZDJpGEEHdOBT9XLssW8Ya7A_iV-AVNq2IUWSnFLdmzXAA-kRzW8rXN1TvAtNe_n0Ugcy7yG3PfeeC8pDgyI-J37xmpooQ2IL8tEgovnawec7oicH0_li4FGGr32QsHD5fl56PzITBLLK3WDjhpTqYrOUT-OXBCZMyXZsZ9qAEqm820uK_96rFUJ8MjJCzMCGCCjl5RdddcdBrouegVYqZNeHK67NHtp8tKXSC5v_gJyPwMr475zpUd5qqZ21HDRCTgoxYdcQvNrlV7FiTl17MpVsGH43YY8G48hasAA7KFw3M3HhybyciZQqWqQN_BImRyk5Ujc2UHMZaFS_XRzUleDU6ULqclHoKeKspOQd3stOVG9bMDhb4VQBz9K_8JNcZQvyns_v8H5elv2x5eHd0tOU8IH0XQvtvdpqj4N3mU5iwNQcnHZpJ3Yb4eYsmjBHBhu3lqBkdK25z_eos8ToEJqbbF9xoFGbfurycrGhk3d5JmH9VVDn03thZaMGhyH1HhBgW_naxQdb8sZYlVvl-kzLodgfekYMgeGyGMnKq236--b33roc3aj7Eii0HgnxQmBku54o54pH1jVAvAU_heRarmeLOY8czHxrTaUAo2E91zuPMc9T9DngWKjUAlQepL_cq6K3LDrHsOYjVQuN_kmZG_hQ92gMDpR8VyRSXt52vn8LUjYwXPZGYTW2eNr47jD9KLeP3whGxrWnX9_uKvJ3O_YEI7gHQQdIhs1SwnWtLhf51SAnuxW_tCxP4M6Hkc82PsDyt1aYAXjG320YxI6yjkFKCkB_h1iSQpoHJRV6nX20o629_nAK807aydLkxFsjr_zfijay14evPjfpqFrl1viOJnywYMNAEoI3dyZXMbHK8D7Gewy6nXUU66jXW37UHiv8m9eqHdxVRpTRx0IUGJeRXs_wjqBXvKSbSde9O9Sf8SaVVcjWYKkWjZO-y0bzngR_yiggx04cdtbSN7pdiOXkFqLiu-1RQqKI11aF4dO3dWkbyw2IJW6e8YwB2Tf7zpqAiFsS19T-eN-MJUmfvLV1Lnmv0TloOU8p9na6VGJWn0pJEgFSCYt1dbY6JBdIHXlbk173u7zyiX80IicdKyW9Qlt1puh4lzrfWpc22QcIoEK7YLKbG2zH8ygIHPl5XZf11mC7S5uGL3RTqPXlWCn1E2fnA=="}}
{"timestamp":"2025-09-22T13:36:20.292Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"$patch = @'\\n*** Begin Patch\\n*** Update File: NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\n@@\\n-using System.Threading.Tasks;\\n+using System.Text;\\n+using System.Threading.Tasks;\\n@@\\n-        private Solver CreateAdvancedSolver()\\n-        {\\n-            var solver = Solver.CreateSolver(SOLVER_TYPE);\\n-            if (solver == null)\\n-            {\\n-                throw new InvalidOperationException(\\\"无法创建增强版线性规划求解器\\\");\\n-            }\\n-\\n-            // 高性能配置\\n-            solver.SetTimeLimit(MAX_SOLVER_TIME_SECONDS * 1000);\\n-            \\n-            // 设置优化参数\\n-            solver.SetSolverSpecificParametersAsString(\\n-                \\\"cuts=1 \\\" +           // 启用割平面\\n-                \\\"heuristics=1 \\\" +     // 启用启发式算法\\n-                \\\"presolve=1 \\\" +       // 启用预处理\\n-                \\\"threads=0\\\"           // 使用所有可用线程\\n-            );\\n-\\n-            _logger.LogInformation(\\\"🔧 高性能求解器创建完成，配置：时间限制{TimeLimit}s，多线程支持\\\", MAX_SOLVER_TIME_SECONDS);\\n-            return solver;\\n-        }\\n+        private Solver CreateAdvancedSolver()\\n+        {\\n+            var solver = Solver.CreateSolver(SOLVER_TYPE);\\n+            if (solver == null)\\n+            {\\n+                throw new InvalidOperationException(\\\"无法创建增强版线性规划求解器\\\");\\n+            }\\n+\\n+            var timeLimitMs = (long)MAX_SOLVER_TIME_SECONDS * 1000L;\\n+            solver.SetTimeLimit(timeLimitMs);\\n+\\n+            var suggestedThreadCount = Math.Max(1, Math.Min(Environment.ProcessorCount, 16));\\n+\\n+            var parameterBuilder = new StringBuilder()\\n+                .AppendLine(\\\"cuts=1\\\")\\n+                .AppendLine(\\\"heuristics=1\\\")\\n+                .AppendLine(\\\"presolve=1\\\")\\n+                .AppendLine($\\\"threads={suggestedThreadCount}\\\");\\n+\\n+            if (OPTIMALITY_TOLERANCE > 0)\\n+            {\\n+                parameterBuilder.AppendLine($\\\"ratioGap={OPTIMALITY_TOLERANCE}\\\");\\n+            }\\n+\\n+            solver.SetSolverSpecificParametersAsString(parameterBuilder.ToString());\\n+\\n+            _logger.LogInformation(\\n+                \\\"🔧 高性能求解器创建完成，配置：时间限制{TimeLimit}s，线程数{ThreadCount}，最优性容忍度{Tolerance}\\\",\\n+                MAX_SOLVER_TIME_SECONDS,\\n+                suggestedThreadCount,\\n+                OPTIMALITY_TOLERANCE);\\n+            return solver;\\n+        }\\n*** End Patch\\n'@; $patch | git apply -v -\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_nn2pLxaEtUaFEzAhALiRv21y"}}
{"timestamp":"2025-09-22T13:36:20.293Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_nn2pLxaEtUaFEzAhALiRv21y","output":"{\"output\":\"error: No valid patches in input (allow with \\\"--allow-empty\\\")\\n\",\"metadata\":{\"exit_code\":1,\"duration_seconds\":0.3}}"}}
{"timestamp":"2025-09-22T13:36:20.293Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:36:27.991Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Evaluating patch formatting and replacement approach**"}}
{"timestamp":"2025-09-22T13:36:29.029Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1755334,"cached_input_tokens":1671808,"output_tokens":16608,"reasoning_output_tokens":10624,"total_tokens":1771942},"last_token_usage":{"input_tokens":48830,"cached_input_tokens":48000,"output_tokens":325,"reasoning_output_tokens":256,"total_tokens":49155},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:36:29.029Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Evaluating patch formatting and replacement approach**"}],"content":null,"encrypted_content":"gAAAAABo0VDdBeeyVrGntLyMSKOH61sy9bls6vlOil-CIG04FOfJfAZxk6lOomY2d5VVvjW8UZNxbKW8Ii7ifxZqk57VN29OigMK5jQl7YhJaYTqdDnRyyovCpoFQ07hRjYGJbP0IbflsVIAHY3Mz4GBxN_6IBKxd0UmNGJM_wtKbPEoGzUg0-Vtm0bDJFe4_ov1f8NBfysDjKr1ojo-skMUUpF6MBat5A2G9tSg5zxS5SgeM0lLE0AqT3o_8QMYd7TGMY2sZ04xPcHfHTzQPVIq2cfDVhtoH_1vMSlFB3--WAnTKQwBOfbORB1HpKCDL1HdGPz2SVd1MxTCAisOkkINDh8hjblTWt2Qv0IFUNgEYeuQot-as71UyQjf7r-zxoLTtzmY7KW8u8BoVP2oHAWwfnjyqkaFARkMBfeBmf6j6Cge6exDRUkqA47topuhmi6QckvcKDSVx08hl3IX1WBuljx7JiRl6HmC-bz5EA-AwXnB9B0kgaxhBhIK2sKJ32f5qblHXsezryYuDTfCQgIYJ1ZaTbNbEPheXykpLYPO1VQCMjmHRK6oSQebJ2IBemtDu-LG8e9RUFwIgMAFsevQrd7m-7hbK1cerSTif_ZZZk2sHeMdDfhKilOmpLuvBHjrIOdugQty514F7wYcLuO19UaAc49Iq9zwQb2iSHBvWDIKY6q99OBxZSjmA09euQW3fU2GeaSzCHVIYAK-WKMHi1QSWHAvNRQ6CcJsnEmHIRvnnzN2WZp5BiEj-eFX6Al260RLi07Z6FpE8b6y0qjEy-YKUobzAu0yYNejytsXFUJtoipZhNxlssgC2SrMUEJ22nb_1k4InVKnI34GR26vcxifPY3TxHTx0OyjO54hHZdYDrMKRcTCDc_Kvx1fBFErlog-JMV7Pbsw18Z_iYQmI1taHsCIPoVnLgKbmTCdpPgP_oH8nUDlCqJ8zercBOzrD5MTkHakLsJ1gNlWEkaRzJA4Jmka9omuHUs3NdLhGP07R7MLiWEbCtQi5AzEhCu-Zl2bhUGJTEuPq0mjnJWaSKLOqpFc4I3s0UgFLvdNLTgGNqvh9K5MfAPIeTd1yZo-f7rB2EE_8kFNrpjLzecBz0xYvCkd9LlKIHlOS0J0jB56M-qAXmmsl_XE0Mf7JYrp5VGehlpMWN9FMUZQnc90HQVCmOeS-vQumUy6eoRgHIANIHh2osIrwPF-bQgB8Frkhf_H5df9XM6kDq9g_UyMN7qLbwP11-L8UdqhZdCIsC4n27fN8DNGX-TGJjZqfBA5W51rB3kkkCG3cEv2gd5i0aduVE5i_cOqhULwncPk3jv3zSOLkd715Q-scowKYZK3oVw3Z_heXdU1xz9FYlpI4SS7_wQdlHy99rL5rEirg7QXXrQ-S4J1BgWb7yNeOSnK8avWpehtb3FLhDosbizc4gS4S0P3ta_LwEWPUs5_wBbPy1nLMfSTouVeT1JZq-5-P1hD9oR8ESzsKcswCJvPYj8Swt_yW4xcQCR271A1b8AhquR286sI_L_tMRITBlYM5m5qYBB_cWz74TIDpRyoKX6T39msoGWtdZaTX63btoHNlPL0FARteVVL0u5MskZ0PDQ4mzUTcKD5fSxd-ksrtKu7wVWiiB-P02vXyKgI-k9js0dvQFuyQ-EecBNi7hdHZLG1vQvwobCMj-He0U7naaLEgSVK-qczDfiw5iJnhXUEhFruxLv5nybnc_x4m-TfzSgTMjzg_XxeBimgViHpi2ftlJDBnUz-Or466hbwZITE5mODui311ol32PlGCASaUDiWhKOaioRPuZ6-VVZuMlFI7L-VJmANMXk-wgAXrvjeVPOTOdksdS7j7E_7TMPqXThd3q_3hmr5OKHF0HOUQZgqqeOcvxcxiCK8Bowhpm6mWL-f6KxBUGAydbpXLPUS-C_1Js5K7AlEQ16VYz3WwpUyHZXABtKcGdrVo722eF23-gEwpr409pQG-6jQC6RYATI2uZKoMw4hQ8asPh52upS3I4XtweXac03uRA88m8mFv1Jj9NWEqK3yc_SSHk6djwzudm-VUBAI4zqX2pNVNOYk-R7KNb9bd3KLKsY9RG69C9w_oeoB-RlMwzQLlQCZePPHPZD6NhP53YCDP8pHbd5YH4N57iEVqFW3mwSDPndCO1Am9h8N9fSWOMNsVeMb0O8VemBhr6iw_egYZckTKWuK2YNZTZ7po7jZd8ljFvJ7zixMUciFSTwWqkJx0CTjS0QiVaCVBBQZCGaE7wkICh-DCY6eIhs2nD_ACfRmTET0SH1B-XT0_NO231nSnLhmwrIBSuaee4M83RqHMnu5_CfhdhNPrDrqZfd3kajPYclwwR_DwcxvXRyU-OtZ5BONVqKq8-K0JX81VJA-sOijodhKch7nAnkm8y3LIH1OaOMI0eTgmVhUBUnhBYdNAEa6UB_QPJ-Mp9TWeg7HIr5q3CeXAHLWbY-DAMhZ_xD3LDGfjTfcaPI2pw8erEtcjfhqK2mfXhm1UvzRf9Ls4WAE4WC8zwXYP1btopU-5dgbGL1bMQ9GMmxPEP8aQqXNsS7eeZPHoKpE9r7p2AAiU3qJP56Lh7jw5uky4Lv2MHFRnApW5t8-n8IhulU9_FIw__V0z7rwQAwEAMQuF63tgyClY3Tp_Poc-jnG7n6llaWWL2jVpW8yCNJQNeSKl1Yta7L5F7Kmp2c3"}}
{"timestamp":"2025-09-22T13:36:29.029Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"Get-Content \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\" -TotalCount 10\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_yME3ViNJyo9veEh9taE1D3ov"}}
{"timestamp":"2025-09-22T13:36:29.029Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_yME3ViNJyo9veEh9taE1D3ov","output":"{\"output\":\"using System;\\r\\nusing System.Collections.Generic;\\r\\nusing System.Linq;\\r\\nusing System.Threading.Tasks;\\r\\nusing Google.OrTools.LinearSolver;\\r\\nusing Microsoft.Extensions.Logging;\\r\\nusing NPP.SmartSchedue.Api.Contracts.Domain.Work;\\r\\nusing NPP.SmartSchedue.Api.Contracts.Domain.Personnel;\\r\\nusing NPP.SmartSchedue.Api.Contracts.Services.Integration.Internal;\\r\\nusing NPP.SmartSchedue.Api.Contracts.Services.Integration.Output;\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.2}}"}}
{"timestamp":"2025-09-22T13:36:29.029Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:36:31.968Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Preparing to insert using directive**"}}
{"timestamp":"2025-09-22T13:36:34.757Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1804670,"cached_input_tokens":1720832,"output_tokens":16766,"reasoning_output_tokens":10624,"total_tokens":1821436},"last_token_usage":{"input_tokens":49336,"cached_input_tokens":49024,"output_tokens":158,"reasoning_output_tokens":0,"total_tokens":49494},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:36:34.757Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Preparing to insert using directive**"}],"content":null,"encrypted_content":"gAAAAABo0VDhwRBJt1l3RQ_kDsxXN-poqxPkNu7zIE0uX61O7pEAusuZn7yG5AnB-sX3-nzzo-hs7691JjzcP5NSKEyJgDbVaFabM31QwpVMR-3WWMUbfNdPGL9Fa36xLY_eC5vLO07oPQSMrrZWIj0hc8ZOkuKBrjeJESAzcBrH32iMiSwDXAOR5qxzOs6fJ_NVkHtqgNfvQVAmGxAH0Ht1UuXbvQn8ZVHFow7nXq1gAlVLoeok59KBbujnJiiMzNqZ7CYIby33alF6zO_XBkAlVricxjYraimFzW-WQhmCw_enRDqHAQ-xhz2Ne599kypDW0wYgHXZjQI1S702QOp19rw5W9A6VHbSzp1NCko9jFvBsNBAOHz_uv2pJOTxCx-M94YwlGX7maK8G-cPHDt6a-HuexHPsuaQvxjqI5BEddU0amYCqq7VQMNfdW8G9MTFqUxyq0TAOyCd5WRDCJwczl36WNE8j0CoFIehyoK2YC9kLHKMROgSZ5F0Bwryg_pPg95aKTHIBa0eaU768HUI55hKNV5YsRNRyUI1_NvDtrADFXsIJRKn8uhyosXxycW3-1IOF3cPL_es62oCSX7-vvPvTPSseBi74dvEO4C0QQlVQGfo3_lsGtOfj24Vqcqs8jYeXaoEGN0wtXHkzvbFOgEhO_Xb5fmU3PumIUGCW_im0EBPca31knlNevSSt4rj858MQEZulkhM_XkYaxfmwh0zzjVnj_mpwebA0V_Ji1XMYNHheLpBGVn9kczybmYXJUJEYK7e2D4nUqAm9GzzfNdzztMznBJx-Tuxlj1wuXu8YJm5GIovd6bT4jqNEbXcBq2E3WxrSNUsOAA0F74ylFQLeYA9F9NaTUSzR-7MyiTsXUBlXJ3zk1pFCPeUbAB7bj9fkagEC__IZJ1wKMmGHFo6vwJ-oKa1RZTMzzqdXC1_jPEK_XojxqeL1LXTmvkwygrwrTMTctKO1O5j1bL_ZYjkulnI_lApi3-9M7wYVMz3qujqqkBOc2mMkR7OmObUnPXOWVLCQCFyY9jEOfI7yE3mBDBcnl8OvvmyrJWsu1A_bwbd2OmeLMtbZnmsSiVBJDTL8SdMchcOWbySLVk5Hq1onqiooA=="}}
{"timestamp":"2025-09-22T13:36:34.757Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"python - <<'PY'\\nfrom pathlib import Path\\npath = Path(r\\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\")\\ntext = path.read_text(encoding='utf-8')\\nneedle = \\\"using System.Linq;\\\\r\\\\n\\\"\\nif \\\"using System.Text;\\\\r\\\\n\\\" not in text:\\n    text = text.replace(needle, needle + \\\"using System.Text;\\\\r\\\\n\\\")\\npath.write_text(text, encoding='utf-8')\\nPY\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_KccqGLz1ifXGgkILTYRawVWW"}}
{"timestamp":"2025-09-22T13:36:34.758Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_KccqGLz1ifXGgkILTYRawVWW","output":"{\"output\":\"����λ�� ��:1 �ַ�: 11\\r\\n+ python - <<'PY'\\r\\n+           ~\\r\\n�ض������������ȱ���ļ��淶��\\r\\n����λ�� ��:1 �ַ�: 10\\r\\n+ python - <<'PY'\\r\\n+          ~\\r\\n��<���������Ϊ����ʹ�ö������ġ�\\r\\n����λ�� ��:1 �ַ�: 11\\r\\n+ python - <<'PY'\\r\\n+           ~\\r\\n��<���������Ϊ����ʹ�ö������ġ�\\r\\n����λ�� ��:2 �ַ�: 1\\r\\n+ from pathlib import Path\\r\\n+ ~~~~\\r\\n�����԰汾�в�֧�֡�from���ؼ��֡�\\r\\n����λ�� ��:6 �ַ�: 3\\r\\n+ if \\\"using System.Text;\\\\r\\\\n\\\" not in text:\\r\\n+   ~\\r\\nif ����еġ�if������ȱ�١�(����\\r\\n����λ�� ��:6 �ַ�: 29\\r\\n+ if \\\"using System.Text;\\\\r\\\\n\\\" not in text:\\r\\n+                             ~~~\\r\\n����ʽ������а�������ı�ǡ�not����\\r\\n����λ�� ��:7 �ַ�: 31\\r\\n+     text = text.replace(needle, needle + \\\"using System.Text;\\\\r\\\\n\\\")\\r\\n+                               ~\\r\\n�����б���ȱ�ٲ�����\\r\\n����λ�� ��:8 �ַ�: 21\\r\\n+ path.write_text(text, encoding='utf-8')\\r\\n+                     ~\\r\\n�����б���ȱ�ٲ�����\\r\\n    + CategoryInfo          : ParserError: (:) [], ParentContainsErrorRecordException\\r\\n    + FullyQualifiedErrorId : MissingFileSpecification\\r\\n \\r\\n\",\"metadata\":{\"exit_code\":1,\"duration_seconds\":0.2}}"}}
{"timestamp":"2025-09-22T13:36:34.758Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:36:43.673Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Adapting Python script execution for PowerShell**"}}
{"timestamp":"2025-09-22T13:36:45.473Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1854680,"cached_input_tokens":1770112,"output_tokens":17226,"reasoning_output_tokens":10944,"total_tokens":1871906},"last_token_usage":{"input_tokens":50010,"cached_input_tokens":49280,"output_tokens":460,"reasoning_output_tokens":320,"total_tokens":50470},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:36:45.473Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Adapting Python script execution for PowerShell**"}],"content":null,"encrypted_content":"gAAAAABo0VDsJ4Yix0xTtW41EA-J0ukctMFwfRTMWBjAC-Dq-RKlqNHCdMlyQCzYrkOYoy6_cYWANjaNmn12pxndUlB54d3rTORKl6YRG_tPozNlAphCECmIzhCtd8AdULn7bkMLt5fd-zKbcfTfj_iZz8bclpvc8CuenjPR3gTn5lONKM92c5TMmK26u2OnL4c92JGRbR5P_bOQ2KFEnJ9-gtrBcLHxiA9O6T_0HLUTszswP3YtEJ1arwE2Mp_c39peXdoR_MLdCgBqPjdcOWzPQrUlodcu7voOW1p1KYQJXWEqaYgWHj3RAqCWtDHm0mc3VVCeDZK76UcYvJ8EVD2kMU6fI_X7XGXmois2ohX_AU54TGDSLAm3doC7en0qjh0u6ezhbeiGanKmoktavpgmeqNZnmW87bubl2SGzBCSCoj_gjc4WiE_KF2I0C-KNxmTA_EU2WaaVbhxmGK4NoK_NeFQ1plO057oFBULYXMvtzV-uE0N5jVTX8eheknX5KIbG7aRQcucLbpVpqO6bMNOcHZeNt-EzmRlqa6YQajiFjEbvE817c9dwrIi_m9Om1s-qc--ZIOsFlxlR380iFoybzCsowfmsNZd9mprqryayWzZOnH2fIjTDAUMY30nE8KmiZO-uF-GQ_goEekYbsrU6k-HCnUcjk0ni5VwjGsE6KAHspHgXdmDDt4rq4vv__SHzT3TU0Tef008a6tQD28A12p5yUExE4IlbE4SNaXA-wFcdQtiC4Q_BI2HlEjsk8GrFl6bQMLKV_-QNwjZAelbQRRh_MMUBVfHXtj-LoQDEd_8VCdTYeFcvWdEF2yeULY4eKOskmPpA28_-bm6-WVFgr_iSzph7u4SdrY6vHU-QqQ9TcQTlrompTv6D9cF0wn4D8Sa6onQZ-ay71LpDOuqCAsNAS3fSLCSzosO7YMgfH_IPdKdockFygIlYhbDWeCUts9NZJRciDrHKZjVpec5XjZuhQ8L57Ai6nimvKR1lyakDhVOPaPwPPDsDxjcP0NXj4Qnow7crdKRnyUGoNJLmQ8OmOd-BM8OCxzVj2pJgzzhASpYbrBpbbsK3eaYlso2PTgPwo3ZVT27Q0chPDZUSCD1_0zBQx4FAq0y5xJ3OI1ueuS22gLVe4w_zi7Ykbl77742VTnPWPOXXe4BYLtQohdJZFCdytuf6ZO42i4L2qvvTJssZRxW0p0_IcV8_wNFnH2QI1pc4A8s7Qg-Y-9gLRP2NWxNcYa5mub_sY5IGKovhdglgi7mqKJyFtKxM4o6-H65-dAtMeq2TTxIHaqh-7kyf5_WhccaNLWhxU-S3-r7RpTVZC-x_TXa5971luHm4kLA2y7IsyLYvYPdMnat6NaV1Ab-ri9VbMacrDtNLSaMIBaR1lzyGMTpsdKU56ormrOq61v2xu2aJx_BxKAjLyYbXePNtiEN3FgtESd0CwoLXlSioZ1t7te9Tun6G1yLUr6Eaf7m5TCc9CBLQr1H81gxho28-xuM3RnFy5jf3QDzT9xq7Fd7WhjNo4d_QpnczuU01htcoSwyYBsahyTTsYPIyxxwBRVLe3kZk4L6WNVDc7DjHvrCaYhAfySEC7A7bUTSFGbULBn2pS_niekKN6sw77_ECzR8usDt0lOHBfFFwBBrhrklY2HEO98QTnXkpxrihg5BNvh5O803R5XaZrlmgKtBjdyKRzFLVJxgUSQddEqn7W7swJA78CJRhL8DJlF0U19HFcQSUxiFfXVCG1bXWzlq_RKZACHJ8tBwsN3ppzc4Frke4Bwht9HYZRkarwqPKj-a_f0ogG4EVNN4P1gwn5Y0gR6s3zdKC8LCXn2XQLGQtnw1gv2pZ91vToM5-F9lCd9rMxflgl2Qt-ik-HZhXCoGErFsJ8Sf_2RESEjg5yqTTWhZTkRj2i2bh3o3H9iGxTTWetOodGtyxPWZs765z_5Tt9o4ukWSqQCL9AvTKI8kcN088NvI9AI33Q-c6KQijAQ53dDNed86QtO2oAL84qufMLRsqO3RHBshs8-yivh2gVWf9K896E15Ij8Sfn1DHW62O8rmKSeKGLkCv3IPtu8cphTVxFnxknQ5VwLW8tIjcNTgEYLkym_xF13MBUkmM-eBCCdvwt7G_G1Av3n5a2DBX3TBD7dQQtKDAr3V5Hf6rzR0d538ogBimUjkBXQVn3Mrh753cjRgg8cc5MHlHKro5THBxdUaN3qf4O2cKlFS9OwweE-1HZv-8pfIoNdgsWyk8zdp_O7atA_nJ67iKZ15fYVrfzUSSrb0ydlUj8bv-12RSBp-rf3HGp_x6qj0044Zyizbjt90VI7rjiNA9kN1WhaJHiwtUZgl5l0uxW958AOiP0hmz_EuJho59HIzdhd-5i0TcDAewkgCDjvzqW_FF3BbRAi1naVzCSRp9TSJE66057ETNwcjdi4I5krl-FPLAUikB8-lCDzLejYIwefPPczGfaAgyW2GUF2ZHTRdYkqvMVdRzw5e-Y-wGFvKBksEoKpl08zewZb2ZjSYKMzpJzZm18N6HBtVO5FIgOwoRI8fY_uF6Ap_EuZ-4SEnxrL3"}}
{"timestamp":"2025-09-22T13:36:45.473Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"python -c \\\"from pathlib import Path; path = Path(r'NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs'); text = path.read_text(encoding='utf-8'); needle = 'using System.Linq;\\\\r\\\\n'; insert = 'using System.Text;\\\\r\\\\n';\\nif insert not in text: text = text.replace(needle, needle + insert); path.write_text(text, encoding='utf-8')\\\"\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_s52CLjkapMaim97IGgzO2Rkf"}}
{"timestamp":"2025-09-22T13:36:45.473Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_s52CLjkapMaim97IGgzO2Rkf","output":"{\"output\":\"python : �޷�����python����ʶ��Ϊ cmdlet���������ű��ļ�������г�������ơ��������Ƶ�ƴд���������·������ȷ��·����ȷ��\\r\\nȻ������һ�Ρ�\\r\\n����λ�� ��:1 �ַ�: 1\\r\\n+ python -c \\\"from pathlib import Path; path = Path(r'NPP.SmartSchedue.A ...\\r\\n+ ~~~~~~\\r\\n    + CategoryInfo          : ObjectNotFound: (python:String) [], CommandNotFoundException\\r\\n    + FullyQualifiedErrorId : CommandNotFoundException\\r\\n \\r\\n\",\"metadata\":{\"exit_code\":1,\"duration_seconds\":0.3}}"}}
{"timestamp":"2025-09-22T13:36:45.473Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:36:49.005Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Checking Python command availability**"}}
{"timestamp":"2025-09-22T13:36:51.936Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1905349,"cached_input_tokens":1820416,"output_tokens":17369,"reasoning_output_tokens":10944,"total_tokens":1922718},"last_token_usage":{"input_tokens":50669,"cached_input_tokens":50304,"output_tokens":143,"reasoning_output_tokens":0,"total_tokens":50812},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:36:51.936Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Checking Python command availability**"}],"content":null,"encrypted_content":"gAAAAABo0VDyymyUY8xhX_Uaog-mvEDk6_Qh9wlJRoxJbXB-veKVKAzz7r436ayyDufpawURpcEh2fNBAmCmkoD5s0GZRO1WEzZvV6TFkJB8bWxlo7jBApm3HOLeyQ1a2PkZ8Cy6QUxTNNM4g6qa9Qnf2YqbBPT7V76MyTuKUzhhBA2lrY4D1s3EvoJUmtbHY-E3tjkkSlNX4TitxdRJRYt5_zSpl9Z2G18rr2gmLS-JdNVeOMso4TIjP_Ev0hZV6nQMTFhYHIC_QlSG-hnYlfeMKJTvq0Sapyl4QtZzafiFVtG1nfAK7EJTaY7YeYn9PqlncCuO2UtY4mcw3eUUl_-SmbpSLbO-EdjIMIG6tnwm9RnI-37yemsIrpH__w3X9B0KwThcxFfjqGMVBLijcGokn9L1jXQYFVhbx98u-fj2Pfmnke78_m5eoL-ZdVLYyUMxn2u9N9n5rAQ2CPC9pRYZ0vpyQjjeR6nBIvpC-O8i_Cx2JcwTPqnpkBV9QvdS0ETLXRQmwA4-jXEewy0jBLhYmjxNYroiVSzK19Yphnzsopn3w5DYlaxxkDt51ezlB6Q2IMHL048tRiH7fNYaP45t7bOSffSYsbehxNM8yFBrPTyZOrt38xSjByFjEk6sOw0mtYgO-q6zRyzIko6CHlufuIBoU_h2BwXw0cppJ1PflxABnGWmsEDIJIewUFsNOs10q538zibl7CFUla7fVarcWAK098RaUBVSGb0quc-2z2OJrW6pvQ8Pc6THCv2yjv60lIrBI0zbi7x9wFqEonDp7I3Kvf-28se2-JAnrCXIy5F7TnYzuCqR161YCivnqXAEI4XDTWZ0P40yL8R3qm0krMNbFv_n594dAey1wbRhNw0mVOFt1-zeCFMZ5i22raEuDI6uX2J-gWzZkgXfA3XztiugIc0j8x4E6UvBTvBoJAG6jrftSsoMHFaAPSaQSQFOMonuUv1iUdT1OhWUlmNvRcS8yX8AyqRRWfnf_Gszb4fmM2OWC9FVVL4ARMzSkBh7FFrFDlgn4-xSiC7WV4Xo_oWBLgCFbzSWgPDw_KCExU91qXn1qKe6u0SVSPZdrs7BrKzJs_DXR39xV2IRSXmysgJ_LUDWCesZL8GSt6KmVhUBw0pA4HLTnd3iiQMlC29i_aVslOWv"}}
{"timestamp":"2025-09-22T13:36:51.936Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"py -c \\\"from pathlib import Path; path = Path(r'NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs'); text = path.read_text(encoding='utf-8'); needle = 'using System.Linq;\\\\r\\\\n'; insert = 'using System.Text;\\\\r\\\\n';\\nif insert not in text:\\n    text = text.replace(needle, needle + insert)\\npath.write_text(text, encoding='utf-8')\\\"\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_tISKHVMB37wl1MZjDew2buja"}}
{"timestamp":"2025-09-22T13:36:51.936Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_tISKHVMB37wl1MZjDew2buja","output":"{\"output\":\"py : �޷�����py����ʶ��Ϊ cmdlet���������ű��ļ�������г�������ơ��������Ƶ�ƴд���������·������ȷ��·����ȷ��Ȼ������\\r\\nһ�Ρ�\\r\\n����λ�� ��:1 �ַ�: 1\\r\\n+ py -c \\\"from pathlib import Path; path = Path(r'NPP.SmartSchedue.Api/S ...\\r\\n+ ~~\\r\\n    + CategoryInfo          : ObjectNotFound: (py:String) [], CommandNotFoundException\\r\\n    + FullyQualifiedErrorId : CommandNotFoundException\\r\\n \\r\\n\",\"metadata\":{\"exit_code\":1,\"duration_seconds\":0.3}}"}}
{"timestamp":"2025-09-22T13:36:51.936Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:36:56.746Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Preparing PowerShell script for file editing**"}}
{"timestamp":"2025-09-22T13:36:58.437Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1956388,"cached_input_tokens":1871104,"output_tokens":17647,"reasoning_output_tokens":11072,"total_tokens":1974035},"last_token_usage":{"input_tokens":51039,"cached_input_tokens":50688,"output_tokens":278,"reasoning_output_tokens":128,"total_tokens":51317},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:36:58.437Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Preparing PowerShell script for file editing**"}],"content":null,"encrypted_content":"gAAAAABo0VD5Gt7JHyQC3dHO7bB1LokZjl-CVi5MocYHcoSIRIIe-aw40w-TZqYrHoyPqSoU6XDFa6xzrLRkc4ok6b60bWPCtxSS8jKtpuKwyR0wFI6aU2rfMEmQ9SeE3u1OxXNQcmDEgNa1HrvHGheQw9NeJgQzB1XsOt29O_XDit7f9rwQckqDY3x5uwmX4yFt5hqC6sh1i5kt4SVi6ggfQ13t02ocADU84xLtqx-ob_wNOUiEGt7ffufFrL-Rosmy7WaH4bw0Bj0C1mRiacAO3J3HdAjxDnt4S0L_jqasU0HHGsm1c99jE7YdAT3EMo8GpOd2Im9aVG78-rPu4b1A1OOVC0WPCmz2y614alcbVHz7vAbKoZCDVCuguHDtvtfjY9tISDHX4-xfbJ3qpflC-wGiV2YtAgeTaXZgSRqH8WXwx-mCsD_QbGOuLaRq9fLCeCdqak_W1NKosvRCw3FzHg2nF7J3avNNSz7Mwd1r6dDJIbCkYaQ7KsBMTWxMOS7ITmD_QwvWDeoYnTIla74KO4jws6e6BUmNIQCv1774YtbzyL0LY8APSdua3oRUN16nTjwCjY18m-15djWlmaI3bBUVV75dx5bV2hA-lNWDvmczcXMQRHVl_afS9FHgPM9O_qRi93HXWqbpDhfYdp1gMHjqmYGAGlbI1hrnJCrA2c4wjydlZKu9jaxYLLFd-kYUQWC1aJZ3-IAEH8s8lgqPkEyXq84HH_iKskb23Qg8soZXE6yhSA5R2MonSXwi8zyKV55OFLW_bGOadfO-6ZqrU8z-FFwabyRsNh65hvrYVi6OkCq4rb9m9Jjm5bALnTnmXtK50CqblFc_eBu0-vWI_eN_Ck890f9-qoLP3__ww7WMKYZ8TXxEnzv0MrwsAzrML7TNJ4um_XA5NjXkFKINIgoRNfdcU51s5VJGVYUd1i5FP4e-kNTwoW1X7SFYzfXg4WAsuFZaGVB7uH8DRPo8u3I5u0o8HTX4Yxyt-CPFjByG1dZiShSDb3c5IRb1vmSNWb74aUGn-mrdgDyB_QyOprC-E_PRHBmu8CEyXfyC-s_Gjo6-cg02502pidiaafkDUb652eQ00c2UuFREbixdKsLZgNNDwEGCGlwEetNM7ztR_H7l8kz03sgS8Q2Pat9JU70z1Q1-9fx1hiuRPsVWfPjAGhDfphg01VDgrjgC4z-LYoMVhTBxFjoCPB4oO4_TppZymNXcGmcps36gIvf3u4u-a3BKmXOk66RiLi3vBBE5KlYUTON_QFfWNn3G82kC2IEM0okdVBgCsI0JcoU-m_a5wpKMYhJ6GKjsS0CNzx6qZ_opsKw2Q4C0smVTbQ4aaVKPtmWOLuDLT8DxijfYQJAC5B3Q_sLnJ9_8l7BTM3rKSdRif0_3CXw6UmByKU8rS_eYkXOJN1q0o6nNgFQrqe8vAXIT-QExaCd1hVfudekDl81UUA7B3r9hnJDS-FsA6ZN0zmgmLA5rOkmDQGuVykO1EFy34iSQ5zi7xAoTKGaqSBLlgx8T2nt0GghPjdQTGvkEkjnOH1FVK-3gAmVWkAucj8X61LKUaZgSlQLshPKXL9y5WbWBALmYl5zDL4thx1B0ZkDPSyDE-bAUZ7ci0QDVC3uUx17BYQ_0QhtBJLDFrwHlH-Y="}}
{"timestamp":"2025-09-22T13:36:58.437Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"$path = \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\"; $content = Get-Content -Path $path -Raw; $needle = \\\"using System.Linq;`r`n\\\"; $insert = \\\"using System.Text;`r`n\\\"; if ($content.Contains($insert) -eq $false) { $content = $content.Replace($needle, $needle + $insert); Set-Content -Path $path -Value $content -Encoding UTF8 }\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_nnVraVAMy4UiToBZscO1YhM4"}}
{"timestamp":"2025-09-22T13:36:58.437Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_nnVraVAMy4UiToBZscO1YhM4","output":"{\"output\":\"\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.2}}"}}
{"timestamp":"2025-09-22T13:36:58.437Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:37:02.276Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Preparing method replacement**"}}
{"timestamp":"2025-09-22T13:37:03.546Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2007759,"cached_input_tokens":1922176,"output_tokens":17807,"reasoning_output_tokens":11136,"total_tokens":2025566},"last_token_usage":{"input_tokens":51371,"cached_input_tokens":51072,"output_tokens":160,"reasoning_output_tokens":64,"total_tokens":51531},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:37:03.546Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Preparing method replacement**"}],"content":null,"encrypted_content":"gAAAAABo0VD_9yBaTQuMC5gw_u0hf9cCkEHFaCA4hH_dkUaU9nlNNtFZJwBZIkPkzxq5Ld8BWUOob6gt5QU4Z0hlIz3E70dwzQYs8mxPWv-kpY91P-HOa8crxc4aZrlLQ0ZF8fz54qyvZoykXS-ze57WH9BhnAoUiicdbG3Rdf5jl147JjLzV-rfCw1icmd3aPQQDABdTi3mYLUOZFecZVZg4GsAPQoUjFKdXQzv0_ineKbl4OIWi_bGllOHYHGMt0t-aYipGXfKdM4BGJjVXkr12e5dnTbMRRJFf9ITOxYYqsIUaQi_wQnmvwb60AsU1WJssiQc1FfYJ_vexXC6fN3r-IjyITSssMS1pm57-D_Hx1geC4kYAVulckS_lNFqETFAFvE_305URxJ0gvL2OY2_lUK3_GuLsaA5FCGbx4g8Au3eFx2fjAtyYjTEeKlTA_HuUYaexpIntutc5jOjkHiGSUXp8u5C1vBDf_4CX63TRn8OvZMJKahxQgi3ls21cYYu2qkAkVMREdrRHxbDOy4sp_RvCCPaA-h4a81M3R7eU2hzBFrpd9t3qwfl0EK1AiEJZlP8lMoAu01LzJU7N25l49_uTkB-LOQZ5W2kEzAyMtvRWxjL--w40BBmLacfyHV57ySX6XTaB3Mrabr48bXftz4ykowAr9JDTANk0dp_GZ_QFZV3zVZehflnIxIqkJtPrLiZcNmt0q91T5I8UgrpGGBXG-Mn5O24VsvIgQbUQ73RddU3iecqDNMsWZ0fsCgt9aifl_StFazcW4uWBgb96LCbJGlGX-_52nJuFxZySItYgxx2tGWiekAnx1MA-FZCefK6j3yQ3QYTBX_4mit5Qif-HK8FLNbZIYXF5uxR1NalrTkMiUyT-flUuzilp1fp4M0yFRYdU4qQBnp8enhdYrpaXNQY_9JrrJaconicZmcwBfc3mI0OliRxrIwqBpof1XngER5SKa69NpwwmtLhY_rjhLKAMS43x4DaiYDsfEAw6Gg-jnmV5_O-eQr4ti0Ri5Kp6aEvFa2S7cuL040iOt-lCdWRLst2GZnEIsM_DYQiiC3VqwDwIY9EiRGqM0XTnL8ikD7pjy3SnjmZ1xjK1wFa-2zcZs20X7O4IEN7iogtH3LmZEw3zSZ4bNpK6S5OjNawRbvv-lenAsNFrqnLm4UkOEwBHuhUmhKuycUG3TVBB8EXk-j6yT8U4USWP5KfQjFmmsfgShxlylELMlWhTioYv6Im7XYNbPP-oLEy8ICPyrotuiMDxhXuNPYq2XTWRZtxS1eIWtVk6uyjrlpiwDdnQ2vlag=="}}
{"timestamp":"2025-09-22T13:37:03.546Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"$path = \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\"; $content = Get-Content -Path $path -Raw; $start = $content.IndexOf(\\\"private Solver CreateAdvancedSolver()\\\"); $snippet = $content.Substring($start, 400); $snippet\"]}","call_id":"call_g0ZxNretKiUuQdtFY0ISbk3j"}}
{"timestamp":"2025-09-22T13:37:03.546Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_g0ZxNretKiUuQdtFY0ISbk3j","output":"{\"output\":\"private Solver CreateAdvancedSolver()\\r\\n        {\\r\\n            var solver = Solver.CreateSolver(SOLVER_TYPE);\\r\\n            if (solver == null)\\r\\n            {\\r\\n                throw new InvalidOperationException(\\\"无法创建增强版线性规划求解器\\\");\\r\\n            }\\r\\n\\r\\n            // 高性能配置\\r\\n            solver.SetTimeLimit(MAX_SOLVER_TIME_SECONDS * 1000);\\r\\n            \\r\\n            // 设置优化参数\\r\\n            sol\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.2}}"}}
{"timestamp":"2025-09-22T13:37:03.546Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:37:05.990Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Requesting additional snippet**"}}
{"timestamp":"2025-09-22T13:37:07.376Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2059421,"cached_input_tokens":1973504,"output_tokens":17903,"reasoning_output_tokens":11136,"total_tokens":2077324},"last_token_usage":{"input_tokens":51662,"cached_input_tokens":51328,"output_tokens":96,"reasoning_output_tokens":0,"total_tokens":51758},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:37:07.376Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Requesting additional snippet**"}],"content":null,"encrypted_content":"gAAAAABo0VEDKbRYDqqUytidw45v6Z8wPB4QFTPK41Hge8gggx2younxXCmDOIAXIOhpIlLaYHDrpTSCqBGzM5p7ognmQcJOgrN7U5lVzk4ue_FA44zJQp-LLjLTTwAaOaU2H8CasqwycDY7gjhc9yZ2WDdhaJhB1kQuTnLkHJv9xrLjNYjrgBu-SddU24zFCB2z-z83sHzt9rXmykI_lZTdXwbFYsRO8vfuY8l8AWwdWDGJ3n1jtg11I4EGDFUF8Z_cIIWqw3dVrYglo7Hgip4mEuHkUpu5AX1-3Ifst_KvSpN8YZo1PlLIYB7_QJFnThdLT9KE3QPDwS-xKyPtS4hWllZ6Y7bgSHENz_YRHsDblNbmvBt87sEEBVQqyNaPfclKyDAPn_DaKxYQUsILO5MtxeOtNVqOSrVHoBoxh-kSw8EZnb_RRs-ye3Ch5LwvejyiCDCbhnW20TAE_OyrcXy9w5iNF45WkeRVOfUX9v1OwTwUbTE1DlQ984DA0pVPcBJfKn9jMzKuRzWgJn1ZMZA3t4qpuPorfyyJykZJbrkfrpBe_u2iH7j-A2LBbqskwHsOYKv6GfsB7P4K23gLGo-IFvptB6rsGFu8ehN_bg_uZ7FyQgnuY2gSqXpRcEee99l57YPM73t2kSYprRWUaKWy1l9OpfX4rGyZikeUem9OigQfA8xWKSQObRDBWiaYbZDNgx-8Xjf9HU1IJUnqsLSJ5h3u8b43KiJ7kIfSrc-Nx4LVkg3q_2p72zkT_8xDIbhIW_Pd2UrRjetxJOk4kgeLwFdmEzJmvQ0_7wuawdX4s1ZkiF9ONwSYJoAprbtipTuKXcM2mUOtHOHNqKdtS3VfCTjJwTShLoJ1W2VDPSTVplc3UojZooJbLeW9aTJ5tTDi8b6H2VJ9"}}
{"timestamp":"2025-09-22T13:37:07.376Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"$path = \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\"; $content = Get-Content -Path $path -Raw; $start = $content.IndexOf(\\\"private Solver CreateAdvancedSolver()\\\"); $snippet = $content.Substring($start, 600); $snippet\"]}","call_id":"call_mAvN2mF6muEgIBQzBigK8beo"}}
{"timestamp":"2025-09-22T13:37:07.376Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_mAvN2mF6muEgIBQzBigK8beo","output":"{\"output\":\"private Solver CreateAdvancedSolver()\\r\\n        {\\r\\n            var solver = Solver.CreateSolver(SOLVER_TYPE);\\r\\n            if (solver == null)\\r\\n            {\\r\\n                throw new InvalidOperationException(\\\"无法创建增强版线性规划求解器\\\");\\r\\n            }\\r\\n\\r\\n            // 高性能配置\\r\\n            solver.SetTimeLimit(MAX_SOLVER_TIME_SECONDS * 1000);\\r\\n            \\r\\n            // 设置优化参数\\r\\n            solver.SetSolverSpecificParametersAsString(\\r\\n                \\\"cuts=1 \\\" +           // 启用割平�?\\n                \\\"heuristics=1 \\\" +     // 启用启发式算�?\\n                \\\"presolve=1 \\\" +       // 启用预处�?\\n     \\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.2}}"}}
{"timestamp":"2025-09-22T13:37:07.377Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:37:09.596Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Requesting additional information**"}}
{"timestamp":"2025-09-22T13:37:10.780Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2111384,"cached_input_tokens":2025088,"output_tokens":17999,"reasoning_output_tokens":11136,"total_tokens":2129383},"last_token_usage":{"input_tokens":51963,"cached_input_tokens":51584,"output_tokens":96,"reasoning_output_tokens":0,"total_tokens":52059},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:37:10.780Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Requesting additional information**"}],"content":null,"encrypted_content":"gAAAAABo0VEGayK0d_HjG31geoVwgtS-1OwLfsWJ3Z6I2YK8d0uSZs0Aty2glbQEFAncHfo9ID_wOuBLD-3KqHu9pN2cwkuEQ9YEhYYjgLwFnlHqs4xdyPV5rMR3EXbXWexw2M_IpwSDVhRx64UahXaoNAP8lgfJtxtcJy6_OcSmXI2UmS99wiPlti6BhrrYXVrc7BM7-drwtnG-x2eQtJVAUuRVyFxnKl1FDdyirPJ8Zsx25NMX489cry_5BkvvO2gEa2_tcm-Ll50b8jYYnILG2nZn17E-XFFO7Yg1gYqgUG9g7sOM5OGxtYn1d_M1j1lNIcOxLoEb3DUsgKXrfOeSiu8RflhyxE5miZ5vNtrRox41NEdf-FCYjKNgGpm2rwV_AYmnHk6Ic0B3HQXheSjcVDYv4eDMWpPaMb0e04yCCTkBQv_W-Sxp6tSwhZu_Xza8VLlLXVH10MbfC5SLfQCrmvlPf9hHqZoz_-njeL7rDroa2QefAPnMOkJyAO3QldTiPQYRFAInOVKHQscJGDfyYB_PSV67o3gBqPru6SyPsTuUXIPC2IVDN2cqnunEZlkYnvVYrhNDSgYQJrudGIM8pvWKa6RGNslx8IB8pKpkxcRMKbKHKF_UsxLwb8eRt-DMRJzdnRjzl-wbalMUoMzQilsj5Ay5Zwip8jVq6vzLlGRETQkz9apFJf5wyF0TTvnX8lcLMQhzgeAxz8hZkIXE2_h-OstMmtc-QJtq30Ia7qp0B_96sj_1UB6xBISiwPHugChPNbuSpGJGDCgY_yeoyt0aXnECAzAsTU1cZQ_0hFwrwavUjtyCQ709UrzVhPnqNSzB_SS6fqIF1m00DgMzbzitA3tmHCXjsmRwhr-Gs5330JSzaRQ="}}
{"timestamp":"2025-09-22T13:37:10.780Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"$path = \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\"; $content = Get-Content -Path $path -Raw; $start = $content.IndexOf(\\\"private Solver CreateAdvancedSolver()\\\"); $snippet = $content.Substring($start, 800); $snippet\"]}","call_id":"call_CuvuXabHQg6N56Z4hgyfqnDD"}}
{"timestamp":"2025-09-22T13:37:10.780Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_CuvuXabHQg6N56Z4hgyfqnDD","output":"{\"output\":\"private Solver CreateAdvancedSolver()\\r\\n        {\\r\\n            var solver = Solver.CreateSolver(SOLVER_TYPE);\\r\\n            if (solver == null)\\r\\n            {\\r\\n                throw new InvalidOperationException(\\\"无法创建增强版线性规划求解器\\\");\\r\\n            }\\r\\n\\r\\n            // 高性能配置\\r\\n            solver.SetTimeLimit(MAX_SOLVER_TIME_SECONDS * 1000);\\r\\n            \\r\\n            // 设置优化参数\\r\\n            solver.SetSolverSpecificParametersAsString(\\r\\n                \\\"cuts=1 \\\" +           // 启用割平�?\\n                \\\"heuristics=1 \\\" +     // 启用启发式算�?\\n                \\\"presolve=1 \\\" +       // 启用预处�?\\n                \\\"threads=0\\\"           // 使用所有可用线�?\\n            );\\r\\n\\r\\n            _logger.LogInformation(\\\"🔧 高性能求解器创建完成，配置：时间限制{TimeLimit}s，多线程支持\\\", MAX_SOLVER_TIME_SECONDS);\\r\\n            ret\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.2}}"}}
{"timestamp":"2025-09-22T13:37:10.780Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:37:13.604Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Noticing incomplete function snippet**"}}
{"timestamp":"2025-09-22T13:37:15.166Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2163706,"cached_input_tokens":2077056,"output_tokens":18118,"reasoning_output_tokens":11136,"total_tokens":2181824},"last_token_usage":{"input_tokens":52322,"cached_input_tokens":51968,"output_tokens":119,"reasoning_output_tokens":0,"total_tokens":52441},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:37:15.166Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Noticing incomplete function snippet**"}],"content":null,"encrypted_content":"gAAAAABo0VEK4TNof2uxWqsUwlwYCZzob6Dci_IDedUdF2gT2v_3xPaLl4HrHBcFyAvCYlqNTsIsJVwnm48eGuG_PXazgkL1ouRyDdvm_W_bgSFD3YFtvYjxpqkS8zEhbHbS2advOmYkD7KkZTE1jN4qqd5cA3ATlv43Pl8KpcA-nUA4PsvMtPwhvtaiVxXWc_dTsBh2zREbWSRoQNk5jeLTFxqy2UkrI3pAvFIZv5-dxT7Hx256DjBLqiPdhh85RdjiABtD7WjccgfP1tO4LyffPkDahwkKIzZiT9ttFTmanzuBbGu5q34nNSio8FDdzr0S09Qn6QCVzXI0qblmQGf5laknB0QAyo2C12nS--o7kEZKtfLrXFek9U3AxCUBCfEVrb5oAZe1hrOWMnT5ggrTVxd3sqL-HAqQq_McssHBdpCJDGxdA3A8DCfkWtNvA46w9nT5NEyS2wHOx4yWc0Tcpb4wOehC5wB5hE38wN-p8IVcfqBfYmEYkcqcE46mQGXylfA2YIxEln46qS-ExLpUxy75HSKtDmfZcIaHGQOiPRRTCOSd9Q1WfBuax-etFYvDgJoSMvg7lyRHzz0jD4O8f0Y8YDrLFT2jEKUdHGLh7cju9TElcFbwWd1sjVRO9dS_h1ekhe9tD209TspM_KWLWmeeDoF0oam8mCR0IG6xiTVS2JhU1Wu9Z8iDKpExflaO4EgpVCok_mMTPwCmBPzorS9YJgkf67San2W896yWGruFezWBLkWbyjsOdsltXz2ZPRJQQyBSjPdXbx2vzmf6yXbxjfe00uFb-e3hP6rN6GlY1mv9x30KShtPSYpi4PUAjJLDadCSR_g0BmA9RRHRS75mQtvR45L3hXoBs132SsXgmXC1UGkMKtc4XUuxB_PMBr-wxNCF194_mbqgSfPU4KbXUPqc0ho4YFrL_tvhTQOSgN6eUr5fFhtsVnWjXfvYYWDqKBJTelbnwrFCJVe9tydgWggL1cA--FnR3t2pIPHnmx9UYVhh-NLl3OpAWfs5SAyRXD2t"}}
{"timestamp":"2025-09-22T13:37:15.166Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"$path = \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\"; $content = Get-Content -Path $path -Raw; $start = $content.IndexOf(\\\"private Solver CreateAdvancedSolver()\\\"); $end = $content.IndexOf(\\\"private Dictionary\\\", $start); $length = $end - $start; $snippet = $content.Substring($start, $length); $snippet\"]}","call_id":"call_ddCHetzyZkjRUYFqtI0Bm7tT"}}
{"timestamp":"2025-09-22T13:37:15.166Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_ddCHetzyZkjRUYFqtI0Bm7tT","output":"{\"output\":\"private Solver CreateAdvancedSolver()\\r\\n        {\\r\\n            var solver = Solver.CreateSolver(SOLVER_TYPE);\\r\\n            if (solver == null)\\r\\n            {\\r\\n                throw new InvalidOperationException(\\\"无法创建增强版线性规划求解器\\\");\\r\\n            }\\r\\n\\r\\n            // 高性能配置\\r\\n            solver.SetTimeLimit(MAX_SOLVER_TIME_SECONDS * 1000);\\r\\n            \\r\\n            // 设置优化参数\\r\\n            solver.SetSolverSpecificParametersAsString(\\r\\n                \\\"cuts=1 \\\" +           // 启用割平�?\\n                \\\"heuristics=1 \\\" +     // 启用启发式算�?\\n                \\\"presolve=1 \\\" +       // 启用预处�?\\n                \\\"threads=0\\\"           // 使用所有可用线�?\\n            );\\r\\n\\r\\n            _logger.LogInformation(\\\"🔧 高性能求解器创建完成，配置：时间限制{TimeLimit}s，多线程支持\\\", MAX_SOLVER_TIME_SECONDS);\\r\\n            return solver;\\r\\n        }\\r\\n\\r\\n        /// <summary>\\r\\n        /// 【Ultra think增强】构建决策变�?- 集成人员班次不可用性的智能变量生成\\r\\n        /// 【核心优化】：在变量创建阶段就排除不可用组合，大幅提升求解效率\\r\\n        /// 【三层优化】：预筛选结�?+ 不可用性检�?+ 评分阈值，实现精确的变量裁�?\\n        /// 【性能提升】：预计减少20-40%的决策变量数量，显著提升求解速度\\r\\n        /// </summary>\\r\\n        \\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.2}}"}}
{"timestamp":"2025-09-22T13:37:15.166Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:37:23.272Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Preparing replacement string for method block**"}}
{"timestamp":"2025-09-22T13:37:30.782Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2216568,"cached_input_tokens":2129408,"output_tokens":19224,"reasoning_output_tokens":11520,"total_tokens":2235792},"last_token_usage":{"input_tokens":52862,"cached_input_tokens":52352,"output_tokens":1106,"reasoning_output_tokens":384,"total_tokens":53968},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:37:30.782Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Preparing replacement string for method block**"}],"content":null,"encrypted_content":"gAAAAABo0VEUisHEzrdDqDQiEizTTv3pl8iKitHVABaJsVH-AMu7Ln7nqmCKk3aA5kEV5yL1Zlcj1pqm29iWSNU3nb5KtM4w7FI1FL7OUc5G_Jbbuq2YsFtRb4WXs96Pdzi_nX3LXmBPSmDgCekn42KCHXog6lfRe5-9qOy9JdlihX5MBclsBLpNTj8MYiZEn1AbVmQCi38txu8Xkv-trMokiAN6C3Mb1CNtT0uVnLl0cRajywdH6nO2dXiTTU1SWwOjtN4xOHOEL8yA66lVW7YHYzFgl7RnR749J_LJfUUpn2Otztjig9NXUh-5epeLvREPIKDzw4aR9vxJjFPvHtcA_dSlsYOPZhcd6E2UCf7wBrA_woZzPNWlZDN_plMTMRGl1rng-sHRvevLMv_ia7yoxj5LdW2K7leFBpuzGo56_Vbux2Aa2t7gV363mNvAdjOToB5HE6oFtN0ncXJc_JPVN9NRiypyh4Wg0FTMjvazjtswAnNzpuK1DJj0tiSXlTGP6a7BSC61jyzz1RAXwzWoKhMgcLWpQCL4_U-VnF7B-NkSTNzB4cqMbH78zZIYH9uMZ5tnIT0W1-xaVZClpPJmHmAh5sgZg1Kx6PReSkflGntWYgx_wOxONDcd5MUZS8Nlm1_pKb-duQl8PjP-_BV3x1_MeCo07F7Pk4NsCeNt4woFCayG2ePOBIpy-wiJ8MuDGvB_UD1mvqjqu_Nv7Kvzev3c0olOJlegQ168vtUyTJlmguVYjFDJ12NqdmUNRaPaiHZUQR_z2BgXrVFtcKtrhjHwkIisbWyPgDNzcOEF1ckaG0VJitR265LFynyV_YmakbPfoA-G_AoJkIdzXUew-Ge9htI0FD87ICb4vOn2gvuxfYSW6JQWINa5zT97b2ggcTE92_r5XN5BXi8f-IGHwYCXbZOPxqJo6h4NT43d8T4oRBC0rgLnrdzEoYbatenU4cVWau2fXTB1o8usOFy4N1EBPiGoIw7ue9y3VkLphdhjmig_Q4n4qxSYVtbrbL1iXOtcSYS8E8VSAWifCSz91fiEGSdlmJcqoW6MXQHYFHQjw_CuHgHSdMh2OtjMRrTZaHqBAkh0vlEcY24G2xc6UNx7HPdYCKvsTTQl1kWng5S6I53xqFth3oZDmbF8WMHsaJDGXaQEIT6dMelI-zQ7i9rwLBtZzdWiA3XhkHbr5ugHqouMwcs-2z6_BB51jgB1NjRBlFFCTMuq_LhgAOvIqXo5-2VIkoKnPUwMhgNFwEG0eljLoTo6098JLTGIlj5Xn4nrJnM0ACFebH0T9L7coQi5CS4C6qNiMCOtfXZd8jKcurHFurgJo9WFXepdoy9p1VKbQNRf-UfOFJrO97dyBId6MfdZTdB61Y4cz_u8PU5hg-K-oWGMe8rZqtKyAD6sRo3BPQLzVKARG-FSNcCBf5v-VMFOAY0xP0wYcCdkMvS2__dGU1YQLfWhgOWyIfkjwSgYRiwpTn3vLY-ZM_UpBab7Bosno98RSP8fhoOlPVVm1POSIQvMruxUwD0xaA9gAaUg9-98q0gdLGjJWSd4IQDefEUCPRgLi4PabXffxPmFzaDn8dApDB3Fps9wSSCzWViaRNKKG2f_yxGUPOeWSTGh-EmgpNz4s1ID3go7_8pp1kfKZiV39oW99Z3Y35EVgPgWIVVCNZm3QDxjR0atyjJDhnOm1NxzSuphvpyQdjvD83NLr2ZUBE5drTMZZUfDTx_uRMI1SG3MWAvf6rGH2hVDUxjtPpGBO0DJsgEO4pmfn8Z-qWLB9FKMKSLcYYLmYmVn7LZ_OSZ0SBXJPT_8CUzZOqYrqCb902IwnMt0C4nNLHHvv4KlubLXjXaz371j2qKKpP9QPKsJYrESdoP3V1P3tQcRMhuMU_6KONQAA9Bq_5-S88qi9onlyw5ocR4WfcLdFy_iMq8w33-CbIlnJYgTb5JIxIuoPQJI6fqmLYMpggaj_QZhlobVFN1R38sgOLVlg74yYCaL40R4_rq_v-u07AmAcd1kZ-D-vTUDveXyOaWHf-75qTzC2-5YtywamR005_zkjslYEB0Xt3nAgKPnMPbXuv8Bkh4g0x_3Q7GD1At-QOnMayP7H-8_sFSRbRfBtji4AB5sJr_nVxfzH1vq7BtByndkQmBW9IIOQ_EURgwuPUynoDQ7vb_TKv2TgIR2do6rK4412Mtdhh0ekfg42WPNNkkQXtUDqzq5EG9didj_8N9yGlLo7ooFS5EZcJ2wbfQGPTbEKluGvGDHAvvtAyMGupHsZncrXp2iJI4XAE1YWqjC0_j4fYUUxqFF8rsguy38esqpM46JGuuW5ZuEWByvF3yYx8_UCPXdOSgcXXNS29LlKToPz5qHhqwS0Wtp4OQs9LU8TCs8LOgQnZew2RWEk1Qw_h3yE8pkD8J8CNB1OMQUS-X_LMasTWl4asWpOqZWyu54nJcUmlpsv_Eo5shlHvpaOnXdulnjY73SNDx-Pnqz80unHpCAfRL7OB_EecxAuk8--wMI-YRI-xDMYy1pZKSA7FnJiqcaa1HadWXOp9jyhqPtpt2OxAvXe4iCrbPS0qJ7PfV_jItKUFj5mINGjvrSJUGE8QBRxzO6qowdiwqu4YGKjYRyF1OlomevYCPkjfBxpHzbuC3Lz2HPo9KqQzLBRbK2SDZChyzA-hjV4kRZ_b9Tmu1FXsbkXmHMH_NSveS86DHmP_psZMw1hVv3YwdKdG5ZL5rqb93KYwHShp4XRclgP13Z2xMTuyFQtOvomf7wUklsGzi76uxi1H1hYHpXKJrDM6AVQsYYsAz8oFDXIHyA3uhJxYWrWi2-I-46cDXQY2e0iQyvxvG7w_4HlNP5Cgs_gJ20A-OQGMXaEy_FDUhjM8IbcGc1W-G5QBxeOnI2t_qMBVGLLE6RHmNI-YHumPkbicSFO_Y-imTNZfDKM0WrAI5t7420hSbDSP0QLMMSO2hKB69ueH0Z12jwdZto3f6wFLupKS2gnl9IawA5bdE3ozBXlao0tBgkcHAwxJS9gzkpURcNzPncIqt_TX2mylH1LDe-Zun1UPtj-0WHtBGZgDIOQ44ufHgZ9Ecytc8v6k06Qk3GnGZV6wcJD7sxach-g7rNm3kTYL-eDz0qFigsavqcmvVkAP2iO0NvlL1n-GJATKQ3Hk-bWBfXUtBrS1z4M6-J87FGZX-vNwJPg12IBpvkK3RlIUtKFfuklcjx1NqqkK8x3f9MdATkJc1_yvAOuTXuqyr44yfL6hN4xt1xDrCBzAeHvld3al1dZoTz17tkbWS2FRqcE5SCBYs5-rid18tiSG3xPbtmOQq50bW9KAlKSAkJxddqnKQDb1nBMtPDYYsjkzhpIXx8qYghDuVq74E_B_IYVoPBGaSI_juf59Szyw19XF61L_mmjcx-2XNGzvcE2w7bbbyT38qMC3xI0M6XQuS2QHM14ejRxNFFqFgNqDDoUey5GPhC8d1t8-HUklsFbquqoQw9-W3xjaQc31tm-kxQEPUE-EGSJH1NQjXO31--4EbqiwHbvpcFwTvgqsFtM-dJsB0_SejptlQPq2TeD5HATjXClwDbdWF1mu647nEbsJlCfuQ3n_vgKYIs-ixNA6wFSv7MvA=="}}
{"timestamp":"2025-09-22T13:37:30.783Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"$path = \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\";$content = Get-Content -Path $path -Raw;$old = @\\\"private Solver CreateAdvancedSolver()\\r\\n        {\\r\\n            var solver = Solver.CreateSolver(SOLVER_TYPE);\\r\\n            if (solver == null)\\r\\n            {\\r\\n                throw new InvalidOperationException(\\\"无法创建增强版线性规划求解器\\\");\\r\\n            }\\r\\n\\r\\n            // 高性能配置\\r\\n            solver.SetTimeLimit(MAX_SOLVER_TIME_SECONDS * 1000);\\r\\n            \\r\\n            // 设置优化参数\\r\\n            solver.SetSolverSpecificParametersAsString(\\r\\n                \\\"cuts=1 \\\" +           // 启用割平面\\r\\n                \\\"heuristics=1 \\\" +     // 启用启发式算法\\r\\n                \\\"presolve=1 \\\" +       // 启用预处理\\r\\n                \\\"threads=0\\\"           // 使用所有可用线程\\r\\n            );\\r\\n\\r\\n            _logger.LogInformation(\\\"🔧 高性能求解器创建完成，配置：时间限制{TimeLimit}s，多线程支持\\\", MAX_SOLVER_TIME_SECONDS);\\r\\n            return solver;\\r\\n        }\\r\\n\\\"@;$new = @\\\"private Solver CreateAdvancedSolver()\\r\\n        {\\r\\n            var solver = Solver.CreateSolver(SOLVER_TYPE);\\r\\n            if (solver == null)\\r\\n            {\\r\\n                throw new InvalidOperationException(\\\"无法创建增强版线性规划求解器\\\");\\r\\n            }\\r\\n\\r\\n            var timeLimitMs = (long)MAX_SOLVER_TIME_SECONDS * 1000L;\\r\\n            solver.SetTimeLimit(timeLimitMs);\\r\\n\\r\\n            var suggestedThreadCount = Math.Max(1, Math.Min(Environment.ProcessorCount, 16));\\r\\n\\r\\n            var parameterBuilder = new StringBuilder()\\r\\n                .AppendLine(\\\"cuts=1\\\")\\r\\n                .AppendLine(\\\"heuristics=1\\\")\\r\\n                .AppendLine(\\\"presolve=1\\\")\\r\\n                .AppendLine($\\\"threads={suggestedThreadCount}\\\");\\r\\n\\r\\n            if (OPTIMALITY_TOLERANCE > 0)\\r\\n            {\\r\\n                parameterBuilder.AppendLine($\\\"ratioGap={OPTIMALITY_TOLERANCE}\\\");\\r\\n            }\\r\\n\\r\\n            solver.SetSolverSpecificParametersAsString(parameterBuilder.ToString());\\r\\n\\r\\n            _logger.LogInformation(\\r\\n                \\\"🔧 高性能求解器创建完成，配置：时间限制{TimeLimit}s，线程数{ThreadCount}，最优性容忍度{Tolerance}\\\",\\r\\n                MAX_SOLVER_TIME_SECONDS,\\r\\n                suggestedThreadCount,\\r\\n                OPTIMALITY_TOLERANCE);\\r\\n            return solver;\\r\\n        }\\r\\n\\\"@;if ($content.Contains($old)) { $content = $content.Replace($old, $new); Set-Content -Path $path -Value $content -Encoding UTF8 } else { Write-Error \\\"Original method block not found.\\\" }\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_14VrmlJfSd4unJdWzrorUc9i"}}
{"timestamp":"2025-09-22T13:37:30.783Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_14VrmlJfSd4unJdWzrorUc9i","output":"{\"output\":\"����λ�� ��:1 �ַ�: 140\\r\\n+ ... Engine.cs\\\";$content = Get-Content -Path $path -Raw;$old = @\\\"private S ...\\r\\n+                                                                 ~\\r\\nhere-string ����������β֮ǰ�����������κ��ַ���\\r\\n����λ�� ��:3 �ַ�: 13\\r\\n+             var solver = Solver.CreateSolver(SOLVER_TYPE);\\r\\n+             ~~~\\r\\n�����԰汾�в�֧�֡�var���ؼ��֡�\\r\\n����λ�� ��:14 �ַ�: 28\\r\\n+                 \\\"cuts=1 \\\" +           // ���ø�ƽ��\\r\\n+                            ~\\r\\n�����ڡ�+������������ṩһ��ֵ����ʽ��\\r\\n����λ�� ��:14 �ַ�: 40\\r\\n+                 \\\"cuts=1 \\\" +           // ���ø�ƽ��\\r\\n+                                        ~\\r\\n�����ڡ�/������������ṩһ��ֵ����ʽ��\\r\\n����λ�� ��:14 �ַ�: 41\\r\\n+                 \\\"cuts=1 \\\" +           // ���ø�ƽ��\\r\\n+                                         ~\\r\\n�����ڡ�/������������ṩһ��ֵ����ʽ��\\r\\n����λ�� ��:14 �ַ�: 42\\r\\n+                 \\\"cuts=1 \\\" +           // ���ø�ƽ��\\r\\n+                                          ~~~~~\\r\\n����ʽ������а�������ı�ǡ����ø�ƽ�桱��\\r\\n����λ�� ��:14 �ַ�: 41\\r\\n+                 \\\"cuts=1 \\\" +           // ���ø�ƽ��\\r\\n+                                         ~\\r\\n����ʽ��ȱ���ҡ�)����\\r\\n����λ�� ��:15 �ַ�: 34\\r\\n+                 \\\"heuristics=1 \\\" +     // ��������ʽ�㷨\\r\\n+                                  ~\\r\\n�����ڡ�+������������ṩһ��ֵ����ʽ��\\r\\n����λ�� ��:15 �ַ�: 40\\r\\n+                 \\\"heuristics=1 \\\" +     // ��������ʽ�㷨\\r\\n+                                        ~\\r\\n�����ڡ�/������������ṩһ��ֵ����ʽ��\\r\\n����λ�� ��:15 �ַ�: 41\\r\\n+                 \\\"heuristics=1 \\\" +     // ��������ʽ�㷨\\r\\n+                                         ~\\r\\n�����ڡ�/������������ṩһ��ֵ����ʽ��\\r\\n��δ�������з����������������Ĵ������ԡ�\\r\\n    + CategoryInfo          : ParserError: (:) [], ParentContainsErrorRecordException\\r\\n    + FullyQualifiedErrorId : UnexpectedCharactersAfterHereStringHeader\\r\\n \\r\\n\",\"metadata\":{\"exit_code\":1,\"duration_seconds\":0.2}}"}}
{"timestamp":"2025-09-22T13:37:30.783Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:37:48.454Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Debugging PowerShell here-string syntax**"}}
{"timestamp":"2025-09-22T13:37:55.694Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2271244,"cached_input_tokens":2182656,"output_tokens":20540,"reasoning_output_tokens":12096,"total_tokens":2291784},"last_token_usage":{"input_tokens":54676,"cached_input_tokens":53248,"output_tokens":1316,"reasoning_output_tokens":576,"total_tokens":55992},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:37:55.694Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Debugging PowerShell here-string syntax**"}],"content":null,"encrypted_content":"[encoded data, 4152 characters]"}}
{"timestamp":"2025-09-22T13:37:55.694Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"$path = \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\"; $content = Get-Content -Path $path -Raw;\\n$old = @\\\"\\nprivate Solver CreateAdvancedSolver()\\r\\n        {\\r\\n            var solver = Solver.CreateSolver(SOLVER_TYPE);\\r\\n            if (solver == null)\\r\\n            {\\r\\n                throw new InvalidOperationException(\\\"无法创建增强版线性规划求解器\\\");\\r\\n            }\\r\\n\\r\\n            // 高性能配置\\r\\n            solver.SetTimeLimit(MAX_SOLVER_TIME_SECONDS * 1000);\\r\\n            \\r\\n            // 设置优化参数\\r\\n            solver.SetSolverSpecificParametersAsString(\\r\\n                \\\"cuts=1 \\\" +           // 启用割平面\\r\\n                \\\"heuristics=1 \\\" +     // 启用启发式算法\\r\\n                \\\"presolve=1 \\\" +       // 启用预处理\\r\\n                \\\"threads=0\\\"           // 使用所有可用线程\\r\\n            );\\r\\n\\r\\n            _logger.LogInformation(\\\"🔧 高性能求解器创建完成，配置：时间限制{TimeLimit}s，多线程支持\\\", MAX_SOLVER_TIME_SECONDS);\\r\\n            return solver;\\r\\n        }\\r\\n\\\"@;\\n$new = @\\\"\\nprivate Solver CreateAdvancedSolver()\\r\\n        {\\r\\n            var solver = Solver.CreateSolver(SOLVER_TYPE);\\r\\n            if (solver == null)\\r\\n            {\\r\\n                throw new InvalidOperationException(\\\"无法创建增强版线性规划求解器\\\");\\r\\n            }\\r\\n\\r\\n            var timeLimitMs = (long)MAX_SOLVER_TIME_SECONDS * 1000L;\\r\\n            solver.SetTimeLimit(timeLimitMs);\\r\\n\\r\\n            var suggestedThreadCount = Math.Max(1, Math.Min(Environment.ProcessorCount, 16));\\r\\n\\r\\n            var parameterBuilder = new StringBuilder()\\r\\n                .AppendLine(\\\"cuts=1\\\")\\r\\n                .AppendLine(\\\"heuristics=1\\\")\\r\\n                .AppendLine(\\\"presolve=1\\\")\\r\\n                .AppendLine($\\\"threads={suggestedThreadCount}\\\");\\r\\n\\r\\n            if (OPTIMALITY_TOLERANCE > 0)\\r\\n            {\\r\\n                parameterBuilder.AppendLine($\\\"ratioGap={OPTIMALITY_TOLERANCE}\\\");\\r\\n            }\\r\\n\\r\\n            solver.SetSolverSpecificParametersAsString(parameterBuilder.ToString());\\r\\n\\r\\n            _logger.LogInformation(\\r\\n                \\\"🔧 高性能求解器创建完成，配置：时间限制{TimeLimit}s，线程数{ThreadCount}，最优性容忍度{Tolerance}\\\",\\r\\n                MAX_SOLVER_TIME_SECONDS,\\r\\n                suggestedThreadCount,\\r\\n                OPTIMALITY_TOLERANCE);\\r\\n            return solver;\\r\\n        }\\r\\n\\\"@;\\nif ($content.Contains($old)) {\\n    $content = $content.Replace($old, $new);\\n    Set-Content -Path $path -Value $content -Encoding UTF8;\\n} else {\\n    Write-Error \\\"Original method block not found.\\\";\\n}\\n\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_vVP6IAUB5emVGJbNp2EpA4rK"}}
{"timestamp":"2025-09-22T13:37:55.694Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_vVP6IAUB5emVGJbNp2EpA4rK","output":"{\"output\":\"$path = \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\"; $content = Get-Content -Path\\r\\n $path -Raw;\\r\\n$old = @\\\"\\r\\nprivate Solver CreateAdvancedSolver()\\r\\n        {\\r\\n            var solver = Solver.CreateSolver(SOLVER_TYPE);\\r\\n            if (solver == null)\\r\\n            {\\r\\n                throw new InvalidOperationException(\\\"�޷�������ǿ�����Թ滮�����\\\");\\r\\n            }\\r\\n            // ����������\\r\\n            solver.SetTimeLimit(MAX_SOLVER_TIME_SECONDS * 1000);\\r\\n            \\r\\n            // �����Ż�����\\r\\n            solver.SetSolverSpecificParametersAsString(\\r\\n                \\\"cuts=1 \\\" +           // ���ø�ƽ��\\r\\n                \\\"heuristics=1 \\\" +     // ��������ʽ�㷨\\r\\n                \\\"presolve=1 \\\" +       // ����Ԥ����\\r\\n                \\\"threads=0\\\"           // ʹ�����п����߳�\\r\\n            );\\r\\n            _logger.LogInformation(\\\"?? �����������������ɣ����ã�ʱ������{TimeLimit}s�����߳�֧��\\\", MAX_SOLVER_TIME_S\\r\\nECONDS);\\r\\n            return solver;\\r\\n        }\\r\\n\\\"@;\\r\\n$new = @\\\"\\r\\nprivate Solver CreateAdvancedSolver()\\r\\n        {\\r\\n            var solver = Solver.CreateSolver(SOLVER_TYPE);\\r\\n            if (solver == null)\\r\\n            {\\r\\n                throw new InvalidOperationException(\\\"�޷�������ǿ�����Թ滮�����\\\");\\r\\n            }\\r\\n            var timeLimitMs = (long)MAX_SOLVER_TIME_SECONDS * 1000L;\\r\\n            solver.SetTimeLimit(timeLimitMs);\\r\\n            var suggestedThreadCount = Math.Max(1, Math.Min(Environment.ProcessorCount, 16));\\r\\n            var parameterBuilder = new StringBuilder()\\r\\n                .AppendLine(\\\"cuts=1\\\")\\r\\n                .AppendLine(\\\"heuristics=1\\\")\\r\\n                .AppendLine(\\\"presolve=1\\\")\\r\\n                .AppendLine($\\\"threads={suggestedThreadCount}\\\");\\r\\n            if (OPTIMALITY_TOLERANCE > 0)\\r\\n            {\\r\\n                parameterBuilder.AppendLine($\\\"ratioGap={OPTIMALITY_TOLERANCE}\\\");\\r\\n            }\\r\\n            solver.SetSolverSpecificParametersAsString(parameterBuilder.ToString());\\r\\n            _logger.LogInformation(\\r\\n                \\\"?? �����������������ɣ����ã�ʱ������{TimeLimit}s���߳���{ThreadCount}�����������̶�{Tolerance}\\\",\\r\\n                MAX_SOLVER_TIME_SECONDS,\\r\\n                suggestedThreadCount,\\r\\n                OPTIMALITY_TOLERANCE);\\r\\n            return solver;\\r\\n        }\\r\\n\\\"@;\\r\\nif ($content.Contains($old)) {\\r\\n    $content = $content.Replace($old, $new);\\r\\n    Set-Content -Path $path -Value $content -Encoding UTF8;\\r\\n} else {\\r\\n    Write-Error \\\"Original method block not found.\\\";\\r\\n}\\r\\n : Original method block not found.\\r\\n    + CategoryInfo          : NotSpecified: (:) [Write-Error], WriteErrorException\\r\\n    + FullyQualifiedErrorId : Microsoft.PowerShell.Commands.WriteErrorException\\r\\n \\r\\n\",\"metadata\":{\"exit_code\":1,\"duration_seconds\":0.3}}"}}
{"timestamp":"2025-09-22T13:37:55.694Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:38:03.204Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Troubleshooting string replacement issues**"}}
{"timestamp":"2025-09-22T13:38:14.080Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2328081,"cached_input_tokens":2237824,"output_tokens":21275,"reasoning_output_tokens":12288,"total_tokens":2349356},"last_token_usage":{"input_tokens":56837,"cached_input_tokens":55168,"output_tokens":735,"reasoning_output_tokens":192,"total_tokens":57572},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:38:14.080Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Troubleshooting string replacement issues**"}],"content":null,"encrypted_content":"gAAAAABo0VE84Xq2ngVnyL6EFaDJIuswgzwj_ajggd74-PIZNRJW5jm8_ITTL4vSgT-pLVHJMtgpadBnvwxXvhhATQsb_VN2WjsMbQUeCiqiYECyEd_b7Vdu0XdSXR0iJp9ExhY_TJecL27lGMUqYKMw9GaK8UkCuF1eUeJuckl9mqfUoOSi__2s8GxFa0GquXnHajt_-P9Ruv8c0rkYOa0VnN5jwcL0qOd63gg6TipHEqtDBkSKjEKWKyDBSJ59tOWHisfyhhuZwSxQwkia904Iat7BFBCsYdVGcjFgmKIsdSQlpTjIA3N3Sjtg3UbyC_7gzTbdJ8UtzI29qAD9GPJM3mKWTzbGrpLvTHsAirw1a0XzbidFRTz2DYl0y_JHmqwx4HbJR0kv2D55Fza2XW2QKu7qIGtG0xGhmSSwRfkheL3QciL46Q8WNdG8UyebpLC23kHCkMOpP8FG4Ofzf-cBGflw5JkJTSQQGRfSEGQ8qwWXxWYYeDXt6OYzEl5A-ToqvfOMJHNcJPk7UBlTli7O8u7zMnw9A2XsmnSqyA3ru0uXCg3Bme75J72lftIrN0xYX6xsFPpdr8c3_Hj9XKED3kfSAmCYHxmSvIQy3dS3_4QT8CFBWPoGkXAdzTxDBYMoe3EvGsxRW03_WWvF5jSC8w8OTLhPrujvMMcQDKpuPC_6ziza1NOnrEVra52jftv-vfdBro5zU_IKYnlpEsFDikZwxPI38aplflnIcQbH9jk6F63jVkjTW5wRDt0vqKCsmWIVTmbNabdTvozbZSHQSwc5jTeD0Zr08A8IwjkNG3lHjjTTPCu3mcSWNtagFzh5IQnV-lAa8mzPbM6rnKMJmZMsl0-WSaSJOqUaliquLhWf_-J_LB9tPfrmdH1Jt3t0DON_Bgh1sg-HXvPtUVihV9zcScVNKZwi0sy_JfBGfwwWAV4SCVJao-NkjnVIJfb4POuLoRAHJT6CX9sxbBebDUhnVS7c-K0m1DqPivEl-ELXJMrR6quR44_wAG0tU2C9Uc47voTvttTQV-tNf9sUpaC46gCyRcQhEA0_xzHGq-X0fPJTsrt1PurLUDavy4oLmOvil9AsU7LSa3Ak-9fUd_DurjqwqUj33GZlr1PspTBAcZ2gs5b9dHL8Xa9R8I5MdVyrWc7eVpfCwe5YD5qhsgJryqgnIpCC16V5aiQgMs1Ar8CJZiZUSCjvhHMIo3dRtlXSa4vLQbeglzSO_J60bu1O_xeegsDlMnhXhQITj1VcowVI2nyVOipTayqUPC3sYXFqi5RaWFeF8qFOiBoImTwSlLLf80GNMLB7XCa_d08Kqtb9kvQn6gBlM1ZEobLQP171cIEWh75gE7CVE5hy3qTOF4c05KNCCpAoP7DeJn6EG-FgulcLE-NPWw1loNZbZKRcespD8F1DUAo6eKSiItv3_ZokQSkNWXxNhn_cfhzl0PX9jbJsZIVbrAnIlQpBvI29e1K5qnjNY-fBhcJHI60y79L4QDkPQQ1WTpM-KJxtPZQbb66ITTjs-H2H9uHg_lwjV0HdWmm9gzsjFKdTcp6DBAoLRKGwjwe1HpdZU6pOss75kMZu6UpY5KKGy-GNQ6V77-er9zI5kAZts980iJKqXUQdFw-jHuVFu__jbI6bsfgmUO1NeJfbxSZuSm5KopvN1WZOHwWusQTBjsScYowWmCTknj8Vu9V91AhRYt_ayNGvIXXvp956joCUJGh6vm7-8ykjvGHUIYFZGwUmgY_nBtu2IAmJVTTKxAT1XAQoXprp7HxQkF-UZRImbpR-NU4TQeXqiQEWi5ec5QqNdIikHwFfm1ShdG0lmpxVdefv1z5pJ5ZmKGhvkclt8mWa-woEjy5U8VE7E5LcynBHM7GhDzanmQH_b5auK0eVe9VMTtgiv7htC5yeiep3qFRL-35CckA8xQgGdQCxkw48hvIuJs2wJ9N_wwI2C0KcIg3I4UuVMkJ-TlgN3JGXytEr2UwAdiWof3jSJWqAl5cTjk0LmYAji55Hm2QQ7Fwd71l2CceahBV_3_45w6l9L5yAlpJszUep5ieAbsdziKdL_dd8e55OtvI3Cl2WRaDv71_TpPWD_8qg4Qcwkz07WRmHEXUZAlhfDcv6dM0iMSkL_EhBhQndKI7O_jLf-FDbCpjb31_Pn1JDm8zAeJvDr1Q_61Alx-5tDZg_QCgZzd6kmFhFiCQb3AFpgd-AMAlhgPdPu2Q0QJPC_E9Z_3ZQ5hWazuFwmCVy_c7WewK2cuhImEIBCNl2xCwbLHXsldrqlDsyD_QKVkpEcXgYP8IHX1SSM7JW9iMVwHm-f0Z8SeayY80NuxU8lqY-HC2LldaDoiMs_XS9zdlKK1xwD8jpnHBOwqz_0xwz"}}
{"timestamp":"2025-09-22T13:38:14.080Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"$path = \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\"; $content = Get-Content -Path $path -Raw;\\n$new = @\\\"\\nprivate Solver CreateAdvancedSolver()\\r\\n        {\\r\\n            var solver = Solver.CreateSolver(SOLVER_TYPE);\\r\\n            if (solver == null)\\r\\n            {\\r\\n                throw new InvalidOperationException(\\\"无法创建增强版线性规划求解器\\\");\\r\\n            }\\r\\n\\r\\n            var timeLimitMs = (long)MAX_SOLVER_TIME_SECONDS * 1000L;\\r\\n            solver.SetTimeLimit(timeLimitMs);\\r\\n\\r\\n            var suggestedThreadCount = Math.Max(1, Math.Min(Environment.ProcessorCount, 16));\\r\\n\\r\\n            var parameterBuilder = new StringBuilder()\\r\\n                .AppendLine(\\\"cuts=1\\\")\\r\\n                .AppendLine(\\\"heuristics=1\\\")\\r\\n                .AppendLine(\\\"presolve=1\\\")\\r\\n                .AppendLine($\\\"threads={suggestedThreadCount}\\\");\\r\\n\\r\\n            if (OPTIMALITY_TOLERANCE > 0)\\r\\n            {\\r\\n                parameterBuilder.AppendLine($\\\"ratioGap={OPTIMALITY_TOLERANCE}\\\");\\r\\n            }\\r\\n\\r\\n            solver.SetSolverSpecificParametersAsString(parameterBuilder.ToString());\\r\\n\\r\\n            _logger.LogInformation(\\r\\n                \\\"🔧 高性能求解器创建完成，配置：时间限制{TimeLimit}s，线程数{ThreadCount}，最优性容忍度{Tolerance}\\\",\\r\\n                MAX_SOLVER_TIME_SECONDS,\\r\\n                suggestedThreadCount,\\r\\n                OPTIMALITY_TOLERANCE);\\r\\n            return solver;\\r\\n        }\\r\\n\\\"@;\\n$pattern = \\\"private Solver CreateAdvancedSolver\\\\(\\\\)\\\\r\\\\n        \\\\{\\\\r\\\\n(?s).*?return solver;\\\\r\\\\n        \\\\}\\\\r\\\\n\\\";\\n$updated = [regex]::Replace($content, $pattern, $new);\\nif ($updated -ne $content) {\\n    Set-Content -Path $path -Value $updated -Encoding UTF8;\\n} else {\\n    Write-Error \\\"Pattern replacement failed.\\\";\\n}\\n\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_MtL4nrLx921zZAGdCUsqZS5u"}}
{"timestamp":"2025-09-22T13:38:14.080Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_MtL4nrLx921zZAGdCUsqZS5u","output":"{\"output\":\"\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.3}}"}}
{"timestamp":"2025-09-22T13:38:14.080Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:38:23.066Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Verifying regex pattern usage**"}}
{"timestamp":"2025-09-22T13:38:23.831Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2385730,"cached_input_tokens":2294784,"output_tokens":21525,"reasoning_output_tokens":12480,"total_tokens":2407255},"last_token_usage":{"input_tokens":57649,"cached_input_tokens":56960,"output_tokens":250,"reasoning_output_tokens":192,"total_tokens":57899},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:38:23.831Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Verifying regex pattern usage**"}],"content":null,"encrypted_content":"gAAAAABo0VFQxASBFpuJf5X2oMrkSWFShPzwQKKoYjWZSoC6jBsLvq7GfOdY4xqz2jwGpgl-fW2hwhhFQdcD3973b7hxyFIj3rT_zVaAQJk4uQqFQ3OC5uxO12tIaS1TozDmEKBhsqogagKMZdzJsSIK2cU0ybtgTEW1hn7rIVzAQMZ-FLZZFfVsHh6IFoUFa1D-Cul5Y3g-368LgfMvF6Zw7-KXj2_4Z3YUOeiVL4_DoWPe7TFhhGqeDgNOL6tFWwHJpqlo6B1CYR2n9kCxMGOo7aATYeCqCX09PKiWfSS2nS4v5dBJUfSlCA0xJ6Muh7E-Areua46jQSAX33Xa_1d9uyCdxC_uMkBsXtD3EVeXM7rhRui1IciH-AQyWcFwW0qftDYL0Z7h9Lap2BpBtobrA5B5YqlekLdpGzmZ1KkOagqVMQwORlxOs-6M7IH6ie1MErzMKrctcZmKzpW9ttBLm_q-Bd-H6pnpEQomgl0LW3dZJeSK4Rg0eYpXnfCAPG_iLbm3B5EgV2ORe7bbTrn8MySNIRnPoKuGDJJmHo7t9wS-Ct2qDpYv-f8lLeQL0vf9SfbL5NYkIq9B-ola8_LecHtR20UVV1DVzW0QQGZCrAfbz2EYvEnrO8GtIG2YYmmJKfVXBEN02ltAexgRdh3jx9d0ZMcG0NpYKWwnCISB1TOcMS4wtpNJwXcuvDMV5jqyXiQq1HORsCrR3KdBZUQ17bm_hB9e9oo4Ia7YpSMGzMMb6sVxTVb8A4vzvVk9SlCZh-Yi7x6CGhZIdAmyPkbWxnmtulHSnRjK2Tj1RnQ5mzSnS5iCNg09snWsq1IbPAtjIO2T-5IQZpWUJrJ6EMCobVCLhbarozoawB5WQN6asoYCpsU6e2QUHu9q8jwOcKMP7eI9O2yqxWSBLk3TkLUwbVFTfz2wxQcWAUBWmn5IMVDl7bv4x68290PLMZDYlC7utCK_PyJZtS58cWH-K7CriGNub2lNwqeS8I6XrhIp6HrVVyG-6c6Sy4ptGhbYAUmyxCphDr7ApM1ZVS2P0cMIojpxC1h6m_NevUywKSCVal2dfyCSsiRowNTlH_weqj-HxEWFR_VGc2iZwQrVq09ugS8Y8qm-JAYN5s12j25ao-W3PbYTGSocNLAMm7AVM44mnrWZp23iLIZgO2fuuudWYWQUQ-6QlrloNcJVFSj3BuHB4gmj7wzlA85-Dc6gHC37m8LPY9zibXXBooGS_eIGDCiQJYhpJ0CG-6Nly1DijyuTbPzbA290YmevGMwkhkCR-hQjkz0KCluPAhIh4-zHn_-SHG-UIuGX9jTE2FBj69pMi3_2syEaLA7bfvpaceXOjb9dnRj6EO7ZsPjUyVIKU8Ty9dxw7xMzVUpDzqrKqGU3BE73ENW-ePr0igT3S0RipiVLlHl4c7mTQrMOMrU9-3dIBFdjAcdxIOYEbRmATFmNEzxkrEvnA9Y8no32T-P4XgLnmUE4cFe5rH97RUnbMkZ84I-uRdrI1lr_sFXwcztDsgOb3yefmtpG4qPyDTy_2gozFibSrjO0_T7-CebZvcHfq4P5A6ZpWK38QXv-aWQTYkcSSTebKBAmrp44lLJ0bHlcoGHKpV5ctGoPtjWb2hVkSFvOf-0iBbv6TufRXh2x27y1yD-fiLDWcsEejypGOoHO5A5vSIwHNB_ZnBSplM3OfPN7QGXJEQ_leDnTo3dR_HaBd7pCUrKswDPFUDAORBG36bzmkmCgnShAvqYS_YZVa_7HT7h0hcirMyMjW_dE-xAz2U8rOz0iS1dpP4DV1VEutkYG_FnamnkEVFSHWrcEXz5Hhv6MQs-8HUVeZzw73mLI8gcJp0jUtuQYGbV2RNl32HUZfe2qW1CdvNTL0HBQb3Q8eWln5ZoR_3w-cTxZ-47bye8ChuFfX1GA_5eYiTKpvUHZbTNGu-MzWepRgU-Xc0v7GCf2XWUsCpnZQ3LHjGTCCzPENkiP4aTt8505J4kxkH6rQcTDsgGz3rY6KAMv0_uWOtqZ-gAPffqQG7Do9z-wWotKwMWEMBdazt97RG03hnqBgBdFOx4anj1Cx1VLyc6WS8CtQqKKN0oF7otwiKwOO6khY_dBGhNmezCUvhtiJ36pJR995zwCkYp4T_mgLUS7UZHNuN9lFQ4inKYST6a6KaSWOhRO1JecsGUdcZEfTLfm"}}
{"timestamp":"2025-09-22T13:38:23.831Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"Get-Content \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\" -TotalCount 160\"]}","call_id":"call_8E2vcSwH8ktR4ROAohYVjWrp"}}
{"timestamp":"2025-09-22T13:38:23.831Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_8E2vcSwH8ktR4ROAohYVjWrp","output":"{\"output\":\"using System;\\r\\nusing System.Collections.Generic;\\r\\nusing System.Linq;\\r\\nusing System.Text;\\r\\nusing System.Threading.Tasks;\\r\\nusing Google.OrTools.LinearSolver;\\r\\nusing Microsoft.Extensions.Logging;\\r\\nusing NPP.SmartSchedue.Api.Contracts.Domain.Work;\\r\\nusing NPP.SmartSchedue.Api.Contracts.Domain.Personnel;\\r\\nusing NPP.SmartSchedue.Api.Contracts.Services.Integration.Internal;\\r\\nusing NPP.SmartSchedue.Api.Contracts.Services.Integration.Output;\\r\\n\\r\\nnamespace NPP.SmartSchedue.Api.Services.Integration.Algorithms\\r\\n{\\r\\n    /// <summary>\\r\\n    /// 增强版线性规划引�?- 实现遗传算法中的所有复杂约�?\\r\\n    /// 核心功能：三级约束体�?+ 多维度目标优�?+ 完整业务规则支持\\r\\n    /// 设计理念：将遗传算法的启发式约束转换为严格的数学约束，实现精确求�?\\r\\n    /// 技术架构：Google OR-Tools + 分层约束建模 + 自适应权重优化\\r\\n    /// 业务价值：提供数学最优解，替代遗传算法的近似解，提升调度质量\\r\\n    /// </summary>\\r\\n    public class LinearProgrammingEngine\\r\\n    {\\r\\n        private readonly ILogger<LinearProgrammingEngine> _logger;\\r\\n        private readonly ShiftRuleValidationEngine _shiftRuleEngine;\\r\\n        \\r\\n        // 求解器配�?- 增强版配置支持复杂约�?\\r\\n        private const string SOLVER_TYPE = \\\"CBC_MIXED_INTEGER_PROGRAMMING\\\";\\r\\n        private const double OPTIMALITY_TOLERANCE = 1e-6;\\r\\n        private const int MAX_SOLVER_TIME_SECONDS = 600; // 增加�?0分钟支持复杂约束\\r\\n        private const int MAX_CONSTRAINT_COUNT = 50000;   // 最大约束数量限�?\\r\\n        \\r\\n        // 约束权重配置 - 对应遗传算法的三级约束体�?\\r\\n        private const double LEVEL1_CONSTRAINT_PENALTY = 1000000.0; // Level 1: 基础约束严厉惩罚\\r\\n        private const double LEVEL2_CONSTRAINT_PENALTY = 100000.0;  // Level 2: 组合约束重度惩罚  \\r\\n        private const double LEVEL3_CONSTRAINT_PENALTY = 10000.0;   // Level 3: 业务约束中度惩罚\\r\\n        private const double FAIRNESS_REWARD_FACTOR = 1000.0;       // 公平性奖励系�?\\r\\n\\r\\n        public LinearProgrammingEngine(\\r\\n            ILogger<LinearProgrammingEngine> logger,\\r\\n            ShiftRuleValidationEngine shiftRuleEngine)\\r\\n        {\\r\\n            _logger = logger ?? throw new ArgumentNullException(nameof(logger));\\r\\n            _shiftRuleEngine = shiftRuleEngine ?? throw new ArgumentNullException(nameof(shiftRuleEngine));\\r\\n        }\\r\\n\\r\\n        /// <summary>\\r\\n        /// 执行增强版线性规划优�?- 实现遗传算法等价的约束体�?\\r\\n        /// 业务流程：构建决策变�?�?三级约束建模 �?多目标优�?�?精确求解 �?解析结果\\r\\n        /// 核心创新：将启发式约束转换为线性约束，实现数学最优解\\r\\n        /// </summary>\\r\\n        public async Task<GlobalOptimizedSolution> OptimizeAsync(GlobalAllocationContext context)\\r\\n        {\\r\\n            var stopwatch = System.Diagnostics.Stopwatch.StartNew();\\r\\n            \\r\\n            try\\r\\n            {\\r\\n                _logger.LogDebug(\\\"🚀 启动增强版线性规划优�?- 任务数：{TaskCount}，人员数：{PersonnelCount}，预筛选缓存：{CacheSize}\\\", \\r\\n                    context.Tasks.Count, context.AvailablePersonnel.Count, context.PrefilterResults.Count);\\r\\n\\r\\n                // 第一步：创建高性能求解�?\\r\\n                using var solver = CreateAdvancedSolver();\\r\\n\\r\\n                // 第二步：构建决策变量矩阵 (x[i,j] = 1表示任务i分配给人员j)\\r\\n                var decisionVariables = BuildDecisionVariables(solver, context);\\r\\n                _logger.LogDebug(\\\"📊 决策变量构建完成 - 变量数量：{VariableCount}\\\", decisionVariables.Count);\\r\\n\\r\\n                // 第三步：构建辅助变量 (支持复杂约束建模)\\r\\n                var auxiliaryVariables = BuildAuxiliaryVariables(solver, context, decisionVariables);\\r\\n                _logger.LogDebug(\\\"🔧 辅助变量构建完成 - 辅助变量数量：{AuxCount}\\\", auxiliaryVariables.Count);\\r\\n\\r\\n                // 第四步：Level 1 基础约束 - 对应遗传算法的基础约束验证\\r\\n                await AddLevel1BasicConstraints(solver, decisionVariables, auxiliaryVariables, context);\\r\\n\\r\\n                // 第五步：Level 2 组合约束 - 对应遗传算法的组合约束验�? \\r\\n                await AddLevel2CombinationConstraints(solver, decisionVariables, auxiliaryVariables, context);\\r\\n\\r\\n                // 第六步：Level 3 业务约束 - 对应遗传算法的业务逻辑约束\\r\\n                await AddLevel3BusinessConstraints(solver, decisionVariables, auxiliaryVariables, context);\\r\\n\\r\\n                // 第七步：公平性约�?- 对应遗传算法的负载均衡机�?\\r\\n                AddFairnessConstraints(solver, decisionVariables, auxiliaryVariables, context);\\r\\n\\r\\n                // 第八步：设置多维度目标函�?- 对应遗传算法的适应度函�?\\r\\n                SetEnhancedObjectiveFunction(solver, decisionVariables, auxiliaryVariables, context);\\r\\n\\r\\n                // 第九步：执行求解\\r\\n                _logger.LogInformation(\\\"🔍 开始求解增强版线性规划模�?..\\\");\\r\\n                var resultStatus = solver.Solve();\\r\\n                \\r\\n                stopwatch.Stop();\\r\\n                \\r\\n                // 第十步：解析和验证结�?\\r\\n                var solution = await ProcessEnhancedSolverResult(solver, decisionVariables, auxiliaryVariables, \\r\\n                    context, resultStatus, stopwatch.ElapsedMilliseconds);\\r\\n                \\r\\n                return solution;\\r\\n            }\\r\\n            catch (Exception ex)\\r\\n            {\\r\\n                stopwatch.Stop();\\r\\n                _logger.LogError(ex, \\\"💥 增强版线性规划优化异常，耗时：{ElapsedMs}ms\\\", stopwatch.ElapsedMilliseconds);\\r\\n                \\r\\n                return CreateFailureSolution(ex.Message, stopwatch.ElapsedMilliseconds);\\r\\n            }\\r\\n        }\\r\\n\\r\\n        #region 求解器和变量构建\\r\\n\\r\\n        /// <summary>\\r\\n        /// 创建高性能求解�?- 支持大规模约束优�?\\r\\n        /// </summary>\\r\\n        private Solver CreateAdvancedSolver()\\r\\n        {\\r\\n            var solver = Solver.CreateSolver(SOLVER_TYPE);\\r\\n            if (solver == null)\\r\\n            {\\r\\n                throw new InvalidOperationException(\\\"�޷�������ǿ�����Թ滮�����\\\");\\r\\n            }\\r\\n\\r\\n            var timeLimitMs = (long)MAX_SOLVER_TIME_SECONDS * 1000L;\\r\\n            solver.SetTimeLimit(timeLimitMs);\\r\\n\\r\\n            var suggestedThreadCount = Math.Max(1, Math.Min(Environment.ProcessorCount, 16));\\r\\n\\r\\n            var parameterBuilder = new StringBuilder()\\r\\n                .AppendLine(\\\"cuts=1\\\")\\r\\n                .AppendLine(\\\"heuristics=1\\\")\\r\\n                .AppendLine(\\\"presolve=1\\\")\\r\\n                .AppendLine($\\\"threads={suggestedThreadCount}\\\");\\r\\n\\r\\n            if (OPTIMALITY_TOLERANCE > 0)\\r\\n            {\\r\\n                parameterBuilder.AppendLine($\\\"ratioGap={OPTIMALITY_TOLERANCE}\\\");\\r\\n            }\\r\\n\\r\\n            solver.SetSolverSpecificParametersAsString(parameterBuilder.ToString());\\r\\n\\r\\n            _logger.LogInformation(\\r\\n                \\\"?? �����������������ɣ����ã�ʱ������{TimeLimit}s���߳���{ThreadCount}�����������̶�{Tolerance}\\\",\\r\\n                MAX_SOLVER_TIME_SECONDS,\\r\\n                suggestedThreadCount,\\r\\n                OPTIMALITY_TOLERANCE);\\r\\n            return solver;\\r\\n        }\\r\\n        /// <summary>\\r\\n        /// 【Ultra think增强】构建决策变�?- 集成人员班次不可用性的智能变量生成\\r\\n        /// 【核心优化】：在变量创建阶段就排除不可用组合，大幅提升求解效率\\r\\n        /// 【三层优化】：预筛选结�?+ 不可用性检�?+ 评分阈值，实现精确的变量裁�?\\r\\n        /// 【性能提升】：预计减少20-40%的决策变量数量，显著提升求解速度\\r\\n        /// </summary>\\r\\n        private Dictionary<(long TaskId, long PersonnelId), Variable> BuildDecisionVariables(\\r\\n            Solver solver, GlobalAllocationContext context)\\r\\n        {\\r\\n            var variables = new Dictionary<(long TaskId, long PersonnelId), Variable>();\\r\\n            var createdCount = 0;\\r\\n            var skippedCount = 0;\\r\\n            var unavailabilitySkippedCount = 0;\\r\\n            \\r\\n            foreach (var task in context.Tasks)\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.3}}"}}
{"timestamp":"2025-09-22T13:38:23.831Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:38:42.362Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Reviewing method insertion and encoding issues**\n\nI'm examining the new method insertion, focusing on log message encoding to avoid console display issues that might show gibberish. I want to confirm the actual file preserves the original Chinese text and emoji despite console limitations. Also, I’m checking spacing conventions around the method and comments, and considering final adjustments to maintain code quality while updating the plan’s progress."}}
{"timestamp":"2025-09-22T13:38:43.388Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2445875,"cached_input_tokens":2352640,"output_tokens":22301,"reasoning_output_tokens":13184,"total_tokens":2468176},"last_token_usage":{"input_tokens":60145,"cached_input_tokens":57856,"output_tokens":776,"reasoning_output_tokens":704,"total_tokens":60921},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:38:43.390Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Reviewing method insertion and encoding issues**\n\nI'm examining the new method insertion, focusing on log message encoding to avoid console display issues that might show gibberish. I want to confirm the actual file preserves the original Chinese text and emoji despite console limitations. Also, I’m checking spacing conventions around the method and comments, and considering final adjustments to maintain code quality while updating the plan’s progress."}],"content":null,"encrypted_content":"[encoded data, 5368 characters]"}}
{"timestamp":"2025-09-22T13:38:43.390Z","type":"response_item","payload":{"type":"function_call","name":"update_plan","arguments":"{\"plan\":[{\"status\":\"completed\",\"step\":\"梳理 CreateAdvancedSolver 当前问题与约束配置风险\"},{\"status\":\"completed\",\"step\":\"实施改造：加强参数配置与健壮性处理\"},{\"status\":\"pending\",\"step\":\"检查代码并总结调整影响\"}]}","call_id":"call_UOIHyF3yxPL2JQzzkUeqelgC"}}
{"timestamp":"2025-09-22T13:38:43.390Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_UOIHyF3yxPL2JQzzkUeqelgC","output":"Plan updated"}}
{"timestamp":"2025-09-22T13:38:43.390Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:38:51.814Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Verifying code replacements and formatting**"}}
{"timestamp":"2025-09-22T13:38:52.189Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2506845,"cached_input_tokens":2413440,"output_tokens":22536,"reasoning_output_tokens":13376,"total_tokens":2529381},"last_token_usage":{"input_tokens":60970,"cached_input_tokens":60800,"output_tokens":235,"reasoning_output_tokens":192,"total_tokens":61205},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:38:52.189Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Verifying code replacements and formatting**"}],"content":null,"encrypted_content":"gAAAAABo0VFr5iOAUBGsqIkPpw4SJXZ4PZJWvt2weISOzpF97E5wU7zYnzkBkueaEGsgrz8UPjvI1z8GDQ5wNoObfbIlGBBD1JDxAltReh8-zojJYEe9RSBMQ0m2XqCSKOVr5Qt1kbqHjcQWHRBQ2fuRjCLs46NjvCQNWZLvKs2xSENJWeAD479fNDFDGuJ8Fbi_iH1n6kjx8RyQpuEwXrbAnxzdaxPhrgghID87dhWyb9GgX2bnh3dW7wSgOzunjSK-r-slp--zbURSeTaw3Cg2tkNM0EuYd2rXpiRS5vkXzQaCtRIi4Do9-dZnZ6i_3gsmHX91dh1cVuhJSkVwd9S1-xVXa-iiKuJ-enKtbVjKaL54H2pA9DdvmS2zFHTvxg4f52_Usig1E7qtJ2lo-6yYwB7oHrF-BpRDX85OlVYIomeAN7KCWfCXKDiKyTW4cUM9iU2l-7sqMyPPLx9zGRVVjexrZYG9a5kgz2j8XdgG4AyzxfM5FWZfhSNULshq2h9sF1uUOi07C6y7NdMAhSV_J-Ij0of6gwg6ATostInGT8VW_yjm2NEOg7tAJWezZ9n9DR5dkOcGiC99lUwfmyIxA7kyNjSM-olae_PI6b2wFwjuiNyxPZrFiuyGGBV26YFnrsH4e5Gvkuy1hzZHkdYiVuDfXRZttOliKKaiKaQpShidaW6G5D6SXuHijEjKMCTPShUOuxUG7HFZYOW0fXug7jAdAoA5Hxi1s-ZZ_M-aVE4jn7XQaAdC_gpD2HYW2udIrYbhkSq_rwZMVDpU7wjVVdxu-ZuwGaZOV81QuTaSxo1ykGAnHv-_dGpTOC7xeQZBJ0Tdso61TjxG7azzs-X4f0BqF3x1vE0zXn7WIePC33RuLxUJknE6CSwZK_MolzWaF0ax7wyBmOSnRwdFba2237_tPlDmnWF0UNc0WT9NpVJQtp-cUu6tchGLX4_DpkAflWHhni4MyyEYtijQqd9PQAqEQPxn2zdJyANCdmn2gZcpdml5PwmXhGLeoZDvdRXNfyqqOOkXxx4AmJSpBmKRh8nT68tq1j0nmTGnEQTlZYQQJ8mWwW-5Cve3mShoAlGzCnWaZf_pCagMMJYkKnLIVRjfQ2ygcMoYfnseN9_2VaMaryrtgycuYDXWVaxYE2vmVfBdzq7xgfadDGvN0FxSsSO0YoXD_qF591TK44tWrKIArCrkDTZBZjD9aeyP4M0mdnRQh8QCf5z8zpqqNMgmTKuaKRE01FisoEOPmu3Mv-bwMZBnBkYGnTRDXWRJ5r5E3G1bQvGGVU5h3tfUgZYhTlbnLtfBf6hIVhwWQHuYtXnE1TxjZuXuQ9nPAnm8oBdlISSDXUFQZ4LCJscSnk1_9ztAcNATdIXrxf7_7-c6t_SsPRY7lg1_RTlI-Io39K-G5NeWbxd3Ost_EkJc9LHgiGuaLJDxm6G34Pxm8BfRoAAX1KwwP02ACs5QELBwmG6ZDIWIQt7IVz8vwP0TSYpNcF6rZYySCsiTWlzPxl4BVGfXFxNWwWL4G0qKpEYA7mwEZzqS-wD4Maelh9rTq5yPox-V3wu-05pHilo4EmiND4uUBHLPEwP-N-uuNQ0frEwNDhYVmWdwn_lounEpHRMxhF-0kKHodUFGlcWeqhrfcgenGuhVUyu6V38qihn5Jo69eV0ZF4Y5zEkZjSjnk1dwFfOjs_7yB1pHHCWc5dBR8Z29OaVwGFeNpSDlTnyWBYMRh-OdTGIjMUQD24Wdtku4yUwYrPk5X5U7mDUfLGuSzqnQDclTw6JXbY-3Ew4fN-ZUM0Po1uAgGIRcI_Tf4IhMItpkIZiIKQbbd_4eoxXJuSkqQUt3CkqB2QDkPEjBXYVmsBNoBXnIiPQK5r7Tak2CsV2tCAR0RVNByebTJ82X0KGqvsLHBw3gkiJ0O3WKVVqj-oaFyNpPV86SJ617ZEYhxL0pHIHthoIPmgy5DVFKcv0hTR1bggpdzNCU8E74XZC5jzAID_3kiRhWjzG4QAyB2Qpoo-QMOIA68Sz5_Fzs2v1XYkbhVXiDzLuUzrPjHbEFcD_MEZJI1G_EuK1TUhsaVM3-SefRycMkIcUseWPggJMsnlK8_vb-qbiOG8HyTba3Lv2H9ySuMkTT0zEoNgLUtgxX_fXdkbfzvezEfQcC_r6Eda9ZMjgBgwogifXjQNKv5L8RAN3_ekr0Wx38iOs6fJ869Sh9ZE6rMViQkN1CPpUve9MLmJrtr1idopQvmc5OQkvarT1ldip8Wk13dI8VdT0dj1KPBMCaFlLIuMOfQgKazJSj3YWT0VIu-2Vta6axEmpMVSAZYoHe30qpD8zmaE4aGyd1NmwSNPZCxwIOtXsuyhnxHeh8UP1i4AXG3sIOyeh9Ta0ZjxwySzshaes-PeyIr0L9cjUryfLkF1fKKMpjnFNWy_KbLPOLWgIDN-PW83kjliYx"}}
{"timestamp":"2025-09-22T13:38:52.189Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"git diff\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_IT2KUzAqW38zzi9McQfJakFG"}}
{"timestamp":"2025-09-22T13:38:52.189Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_IT2KUzAqW38zzi9McQfJakFG","output":"{\"output\":\"warning: in the working copy of '.claude/settings.local.json', LF will be replaced by CRLF the next time Git touches it\\nwarning: in the working copy of '.idea/.idea.NPP.SmartSchedue/.idea/workspace.xml', LF will be replaced by CRLF the next time Git touches it\\nwarning: in the working copy of 'NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs', LF will be replaced by CRLF the next time Git touches it\\ndiff --git a/.claude/settings.local.json b/.claude/settings.local.json\\nindex e3aaf9a..646b096 100644\\n--- a/.claude/settings.local.json\\n+++ b/.claude/settings.local.json\\n@@ -23,7 +23,28 @@\\n       \\\"Bash(dotnet run:*)\\\",\\n       \\\"Bash(mkdir:*)\\\",\\n       \\\"Bash(git restore:*)\\\",\\n-      \\\"Bash(ls:*)\\\"\\n+      \\\"Bash(ls:*)\\\",\\n+      \\\"WebSearch\\\",\\n+      \\\"Bash(where claude)\\\",\\n+      \\\"Bash(claude mcp --help)\\\",\\n+      \\\"Bash(claude mcp list)\\\",\\n+      \\\"Bash(claude mcp add context7 -- npx -y @upstash/context7-mcp --api-key ctx7sk-a7e77440-3e75-4b24-9462-642a8c69fec2)\\\",\\n+      \\\"Read(/C:\\\\\\\\Users\\\\\\\\Asoka\\\\\\\\.claude/**)\\\",\\n+      \\\"Read(/C:\\\\\\\\Users\\\\\\\\Asoka\\\\\\\\.claude/**)\\\",\\n+      \\\"Bash(npx -y @modelcontextprotocol/server-memory)\\\",\\n+      \\\"Bash(claude mcp add memory -- npx -y @modelcontextprotocol/server-memory)\\\",\\n+      \\\"Read(/C:\\\\\\\\GitCode\\\\\\\\paiban\\\\\\\\.claude/**)\\\",\\n+      \\\"Read(/C:\\\\\\\\Users\\\\\\\\Asoka\\\\\\\\.claude/**)\\\",\\n+      \\\"Read(/C:\\\\\\\\Users\\\\\\\\Asoka\\\\\\\\.claude/**)\\\",\\n+      \\\"Read(/C:\\\\\\\\Users\\\\\\\\Asoka\\\\\\\\.claude/**)\\\",\\n+      \\\"Read(/C:\\\\\\\\GitCode\\\\\\\\paiban\\\\\\\\NPP.SmartSchedue.Api.Contracts\\\\\\\\Services\\\\\\\\Integration/**)\\\",\\n+      \\\"Read(/C:\\\\\\\\GitCode\\\\\\\\paiban\\\\\\\\NPP.SmartSchedue.Api\\\\\\\\Services\\\\\\\\Integration/**)\\\",\\n+      \\\"Read(/C:\\\\\\\\GitCode\\\\\\\\paiban\\\\\\\\NPP.SmartSchedue.Api\\\\\\\\Services\\\\\\\\Integration/**)\\\",\\n+      \\\"Read(/C:\\\\\\\\GitCode\\\\\\\\paiban\\\\\\\\NPP.SmartSchedue.Api.Contracts\\\\\\\\Services\\\\\\\\Integration/**)\\\",\\n+      \\\"Read(/C:\\\\\\\\GitCode\\\\\\\\paiban\\\\\\\\NPP.SmartSchedue.Api.Contracts\\\\\\\\Domain\\\\\\\\Work/**)\\\",\\n+      \\\"Read(/C:\\\\\\\\GitCode\\\\\\\\paiban\\\\\\\\NPP.SmartSchedue.Api\\\\\\\\Services\\\\\\\\Work/**)\\\",\\n+      \\\"Read(/C:\\\\\\\\GitCode\\\\\\\\paiban\\\\\\\\NPP.SmartSchedue.Api\\\\\\\\Services\\\\\\\\Work/**)\\\",\\n+      \\\"Read(/C:\\\\\\\\GitCode\\\\\\\\paiban\\\\\\\\NPP.SmartSchedue.Api.Contracts\\\\\\\\Domain\\\\\\\\Work/**)\\\"\\n     ],\\n     \\\"deny\\\": []\\n   }\\ndiff --git a/.idea/.idea.NPP.SmartSchedue/.idea/vcs.xml b/.idea/.idea.NPP.SmartSchedue/.idea/vcs.xml\\nindex c2365ab..94a25f7 100644\\n--- a/.idea/.idea.NPP.SmartSchedue/.idea/vcs.xml\\n+++ b/.idea/.idea.NPP.SmartSchedue/.idea/vcs.xml\\n@@ -1,6 +1,6 @@\\n <?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?>\\n <project version=\\\"4\\\">\\n   <component name=\\\"VcsDirectoryMappings\\\">\\n-    <mapping directory=\\\"$PROJECT_DIR$/../../..\\\" vcs=\\\"Git\\\" />\\n+    <mapping directory=\\\"$PROJECT_DIR$\\\" vcs=\\\"Git\\\" />\\n   </component>\\n </project>\\n\\\\ No newline at end of file\\ndiff --git a/.idea/.idea.NPP.SmartSchedue/.idea/workspace.xml b/.idea/.idea.NPP.SmartSchedue/.idea/workspace.xml\\nindex acefcd0..c21c1c5 100644\\n--- a/.idea/.idea.NPP.SmartSchedue/.idea/workspace.xml\\n+++ b/.idea/.idea.NPP.SmartSchedue/.idea/workspace.xml\\n@@ -10,12 +10,9 @@\\n   </component>\\n   <component name=\\\"ChangeListManager\\\">\\n     <list default=\\\"true\\\" id=\\\"635f35ee-190e-4c9a-82f7-ee1c8f1bea95\\\" name=\\\"更改\\\" comment=\\\"\\\">\\n+      <change beforePath=\\\"$PROJECT_DIR$/.claude/settings.local.json\\\" beforeDir=\\\"false\\\" afterPath=\\\"$PROJECT_DIR$/.claude/settings.local.json\\\" afterDir=\\\"false\\\" />\\n+      <change beforePath=\\\"$PROJECT_DIR$/.idea/.idea.NPP.SmartSchedue/.idea/vcs.xml\\\" beforeDir=\\\"false\\\" afterPath=\\\"$PROJECT_DIR$/.idea/.idea.NPP.SmartSchedue/.idea/vcs.xml\\\" afterDir=\\\"false\\\" />\\n       <change beforePath=\\\"$PROJECT_DIR$/.idea/.idea.NPP.SmartSchedue/.idea/workspace.xml\\\" beforeDir=\\\"false\\\" afterPath=\\\"$PROJECT_DIR$/.idea/.idea.NPP.SmartSchedue/.idea/workspace.xml\\\" afterDir=\\\"false\\\" />\\n-      <change beforePath=\\\"$PROJECT_DIR$/ExecutiveSummary.md\\\" beforeDir=\\\"false\\\" />\\n-      <change beforePath=\\\"$PROJECT_DIR$/GeneticAlgorithmPerformanceAnalysis.md\\\" beforeDir=\\\"false\\\" />\\n-      <change beforePath=\\\"$PROJECT_DIR$/GeneticAlgorithmTestPlan.md\\\" beforeDir=\\\"false\\\" />\\n-      <change beforePath=\\\"$PROJECT_DIR$/NPP.SmartSchedue.Api/NPP.SmartSchedue.Api.xml\\\" beforeDir=\\\"false\\\" afterPath=\\\"$PROJECT_DIR$/NPP.SmartSchedue.Api/NPP.SmartSchedue.Api.xml\\\" afterDir=\\\"false\\\" />\\n-      <change beforePath=\\\"$PROJECT_DIR$/PerformanceOptimizationRecommendations.md\\\" beforeDir=\\\"false\\\" />\\n     </list>\\n     <option name=\\\"SHOW_DIALOG\\\" value=\\\"false\\\" />\\n     <option name=\\\"HIGHLIGHT_CONFLICTS\\\" value=\\\"true\\\" />\\n@@ -31,7 +28,7 @@\\n         <entry key=\\\"$PROJECT_DIR$/../../..\\\" value=\\\"dev_schedule_2\\\" />\\n       </map>\\n     </option>\\n-    <option name=\\\"RECENT_GIT_ROOT_PATH\\\" value=\\\"$PROJECT_DIR$/../../..\\\" />\\n+    <option name=\\\"RECENT_GIT_ROOT_PATH\\\" value=\\\"$PROJECT_DIR$\\\" />\\n   </component>\\n   <component name=\\\"GitLabMergeRequestFiltersHistory\\\">{\\n   &quot;lastFilter&quot;: {\\n@@ -78,30 +75,30 @@\\n     <option name=\\\"hideEmptyMiddlePackages\\\" value=\\\"true\\\" />\\n     <option name=\\\"showLibraryContents\\\" value=\\\"true\\\" />\\n   </component>\\n-  <component name=\\\"PropertiesComponent\\\"><![CDATA[{\\n-  \\\"keyToString\\\": {\\n-    \\\".NET 启动设置配置文件.NPP.SmartSchedue.Host.executor\\\": \\\"Debug\\\",\\n-    \\\"ModuleVcsDetector.initialDetectionPerformed\\\": \\\"true\\\",\\n-    \\\"RunOnceActivity.ShowReadmeOnStart\\\": \\\"true\\\",\\n-    \\\"RunOnceActivity.Ter\\n[... omitted 2435 of 2691 lines ...]\\n\\n鍙敤鎬у紓甯?- 浠诲姟{TaskId}浜哄憳{PersonnelId}锛岄粯璁や负涓嶅彲鐢?, \\n                     task.Id, personnelId);\\n-                return true; // 异常情况下保守处理，标记为不可用\\n+                return true; // 寮傚父鎯呭喌涓嬩繚瀹堝鐞嗭紝鏍囪涓轰笉鍙敤\\n             }\\n         }\\n \\n         /// <summary>\\n-        /// 【Ultra think方法】检查人员在指定任务时间是否不可用（异步版本）\\n-        /// 【扩展支持】：为未来集成更复杂的不可用性检查逻辑预留接口\\n+        /// 銆怳ltra think鏂规硶銆戞鏌ヤ汉鍛樺湪鎸囧畾浠诲姟鏃堕棿鏄惁涓嶅彲鐢紙寮傛鐗堟湰锛?\\n+        /// 銆愭墿灞曟敮鎸併€戯細涓烘湭鏉ラ泦鎴愭洿澶嶆潅鐨勪笉鍙敤鎬ф鏌ラ€昏緫棰勭暀鎺ュ彛\\n         /// </summary>\\n         private async Task<bool> IsPersonnelUnavailableForTaskAsync(WorkOrderEntity task, long personnelId, GlobalAllocationContext context)\\n         {\\n-            // 目前直接调用同步版本，保持异步接口以便未来扩展\\n+            // 鐩墠鐩存帴璋冪敤鍚屾鐗堟湰锛屼繚鎸佸紓姝ユ帴鍙ｄ互渚挎湭鏉ユ墿灞?\\n             await Task.CompletedTask;\\n             return IsPersonnelUnavailableForTask(task, personnelId, context);\\n         }\\n@@ -2319,7 +2330,7 @@ namespace NPP.SmartSchedue.Api.Services.Integration.Algorithms\\n     }\\n \\n     /// <summary>\\n-    /// 人员任务矩阵 - 支持高效的关联查询\\n+    /// 浜哄憳浠诲姟鐭╅樀 - 鏀寔楂樻晥鐨勫叧鑱旀煡璇?\\n     /// </summary>\\n     public class PersonnelTaskMatrix\\n     {\\n@@ -2328,7 +2339,7 @@ namespace NPP.SmartSchedue.Api.Services.Integration.Algorithms\\n     }\\n \\n     /// <summary>\\n-    /// 时间窗口定义\\n+    /// 鏃堕棿绐楀彛瀹氫箟\\n     /// </summary>\\n     public class TimeWindow : IEquatable<TimeWindow>\\n     {\\n@@ -2350,26 +2361,26 @@ namespace NPP.SmartSchedue.Api.Services.Integration.Algorithms\\n     }\\n \\n     /// <summary>\\n-    /// 冲突严重程度枚举\\n+    /// 鍐茬獊涓ラ噸绋嬪害鏋氫妇\\n     /// </summary>\\n     public enum ConflictSeverity\\n     {\\n-        None = 0,        // 无冲突\\n-        Low = 1,         // 轻微冲突\\n-        Medium = 2,      // 中等冲突\\n-        High = 3,        // 严重冲突\\n-        Critical = 4     // 关键冲突\\n+        None = 0,        // 鏃犲啿绐?\\n+        Low = 1,         // 杞诲井鍐茬獊\\n+        Medium = 2,      // 涓瓑鍐茬獊\\n+        High = 3,        // 涓ラ噸鍐茬獊\\n+        Critical = 4     // 鍏抽敭鍐茬獊\\n     }\\n \\n     /// <summary>\\n-    /// WorkOrderEntity扩展方法 - 为LinearProgrammingEngine提供辅助功能\\n+    /// WorkOrderEntity鎵╁睍鏂规硶 - 涓篖inearProgrammingEngine鎻愪緵杈呭姪鍔熻兘\\n     /// </summary>\\n     public static class WorkOrderEntityExtensions\\n     {\\n         /// <summary>\\n-        /// 【深度实现】为验证目的克隆WorkOrderEntity\\n-        /// 【业务思考】：在线性规划验证过程中，需要模拟分配的临时任务对象\\n-        /// 【技术要点】：仅复制验证所需的关键字段，避免整体对象克隆的性能开销\\n+        /// 銆愭繁搴﹀疄鐜般€戜负楠岃瘉鐩殑鍏嬮殕WorkOrderEntity\\n+        /// 銆愪笟鍔℃€濊€冦€戯細鍦ㄧ嚎鎬ц鍒掗獙璇佽繃绋嬩腑锛岄渶瑕佹ā鎷熷垎閰嶇殑涓存椂浠诲姟瀵硅薄\\n+        /// 銆愭妧鏈鐐广€戯細浠呭鍒堕獙璇佹墍闇€鐨勫叧閿瓧娈碉紝閬垮厤鏁翠綋瀵硅薄鍏嬮殕鐨勬€ц兘寮€閿€\\n         /// </summary>\\n         public static WorkOrderEntity CloneForValidation(this WorkOrderEntity original)\\n         {\\n@@ -2388,8 +2399,8 @@ namespace NPP.SmartSchedue.Api.Services.Integration.Algorithms\\n                 ComplexityLevel = original.ComplexityLevel,\\n                 EstimatedHours = original.EstimatedHours,\\n                 Status = original.Status,\\n-                AssignedPersonnelId = original.AssignedPersonnelId, // 这个将被修改为模拟分配的人员ID\\n-                // 关联对象也需要复制\\n+                AssignedPersonnelId = original.AssignedPersonnelId, // 杩欎釜灏嗚淇敼涓烘ā鎷熷垎閰嶇殑浜哄憳ID\\n+                // 鍏宠仈瀵硅薄涔熼渶瑕佸鍒?\\n                 ShiftEntity = original.ShiftEntity,\\n                 ProcessEntity = original.ProcessEntity,\\n                 WorkOrderFLPersonnels = original.WorkOrderFLPersonnels\\n@@ -2398,7 +2409,7 @@ namespace NPP.SmartSchedue.Api.Services.Integration.Algorithms\\n     }\\n \\n     /// <summary>\\n-    /// 解质量指标\\n+    /// 瑙ｈ川閲忔寚鏍?\\n     /// </summary>\\n     public class SolutionQualityMetrics\\n     {\\n@@ -2409,4 +2420,5 @@ namespace NPP.SmartSchedue.Api.Services.Integration.Algorithms\\n         public double ConstraintSatisfactionRate { get; set; }\\n         public List<string> ViolationDetails { get; set; } = new();\\n     }\\n-}\\n\\\\ No newline at end of file\\n+}\\n+\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.2}}"}}
{"timestamp":"2025-09-22T13:38:52.189Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:39:21.558Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Diagnosing encoding-related file corruption**\n\nThis huge diff looks caused by encoding mismatches from using `Set-Content -Encoding UTF8`, which surprisingly altered the file’s characters into gibberish likely due to BOM and code page issues. I need to carefully verify actual file encoding and content, then revert the unintended changes and reapply my intended edits more cautiously to avoid mass corruption."}}
{"timestamp":"2025-09-22T13:39:23.036Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2571672,"cached_input_tokens":2474624,"output_tokens":23797,"reasoning_output_tokens":14592,"total_tokens":2595469},"last_token_usage":{"input_tokens":64827,"cached_input_tokens":61184,"output_tokens":1261,"reasoning_output_tokens":1216,"total_tokens":66088},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:39:23.036Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Diagnosing encoding-related file corruption**\n\nThis huge diff looks caused by encoding mismatches from using `Set-Content -Encoding UTF8`, which surprisingly altered the file’s characters into gibberish likely due to BOM and code page issues. I need to carefully verify actual file encoding and content, then revert the unintended changes and reapply my intended edits more cautiously to avoid mass corruption."}],"content":null,"encrypted_content":"[encoded data, 8568 characters]"}}
{"timestamp":"2025-09-22T13:39:23.037Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"git status --short\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_iaHnmLklwqV8HzPeo5OjCA3h"}}
{"timestamp":"2025-09-22T13:39:23.037Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_iaHnmLklwqV8HzPeo5OjCA3h","output":"{\"output\":\" M .claude/settings.local.json\\n M .idea/.idea.NPP.SmartSchedue/.idea/vcs.xml\\n M .idea/.idea.NPP.SmartSchedue/.idea/workspace.xml\\n M NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\n?? AGENTS.md\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.2}}"}}
{"timestamp":"2025-09-22T13:39:23.037Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:39:38.459Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Evaluating safe file restoration approach**"}}
{"timestamp":"2025-09-22T13:39:39.819Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2637859,"cached_input_tokens":2539392,"output_tokens":24454,"reasoning_output_tokens":15168,"total_tokens":2662313},"last_token_usage":{"input_tokens":66187,"cached_input_tokens":64768,"output_tokens":657,"reasoning_output_tokens":576,"total_tokens":66844},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:39:39.819Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Evaluating safe file restoration approach**"}],"content":null,"encrypted_content":"[encoded data, 5004 characters]"}}
{"timestamp":"2025-09-22T13:39:39.819Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"git show HEAD:\\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\" | Select-String -Pattern \\\"CreateAdvancedSolver\\\" -Context 0,40\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_p6vkbQG8yzX42COjS90VBCwl"}}
{"timestamp":"2025-09-22T13:39:39.819Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_p6vkbQG8yzX42COjS90VBCwl","output":"{\"output\":\"\\r\\n>                 // 第一步：创建高性能求解�?                using var solver = CreateAdvancedSolver();\\r\\n  \\r\\n                  // 第二步：构建决策变量矩阵 (x[i,j] = 1表示任务i分配给人员j)\\r\\n                  var decisionVariables = BuildDecisionVariables(solver, context);\\r\\n                  _logger.LogDebug(\\\"📊 决策变量构建完成 - 变量数量：{VariableCount}\\\", decisionVariables.\\r\\nCount);\\r\\n  \\r\\n                  // 第三步：构建辅助变量 (支持复杂约束建模)\\r\\n                  var auxiliaryVariables = BuildAuxiliaryVariables(solver, context, decisionVariables);\\r\\n                  _logger.LogDebug(\\\"🔧 辅助变量构建完成 - 辅助变量数量：{AuxCount}\\\", auxiliaryVariable\\r\\ns.Count);\\r\\n  \\r\\n                  // 第四步：Level 1 基础约束 - 对应遗传算法的基础约束验证\\r\\n                  await AddLevel1BasicConstraints(solver, decisionVariables, auxiliaryVariables, context);\\r\\n  \\r\\n                  // 第五步：Level 2 组合约束 - 对应遗传算法的组合约束验�? \\r\\n                  await AddLevel2CombinationConstraints(solver, decisionVariables, auxiliaryVariables, context);\\r\\n  \\r\\n                  // 第六步：Level 3 业务约束 - 对应遗传算法的业务逻辑约束\\r\\n                  await AddLevel3BusinessConstraints(solver, decisionVariables, auxiliaryVariables, context);\\r\\n  \\r\\n                  // 第七步：公平性约�?- 对应遗传算法的负载均衡机�?                AddFairnessConstra\\r\\nints(solver, decisionVariables, auxiliaryVariables, context);\\r\\n  \\r\\n                  // 第八步：设置多维度目标函�?- 对应遗传算法的适应度函�?                SetEnhan\\r\\ncedObjectiveFunction(solver, decisionVariables, auxiliaryVariables, context);\\r\\n  \\r\\n                  // 第九步：执行求解\\r\\n                  _logger.LogInformation(\\\"🔍 开始求解增强版线性规划模�?..\\\");\\r\\n                  var resultStatus = solver.Solve();\\r\\n                  \\r\\n                  stopwatch.Stop();\\r\\n                  \\r\\n                  // 第十步：解析和验证结�?                var solution = await ProcessEnhancedSolverResult(s\\r\\nolver, decisionVariables, auxiliaryVariables, \\r\\n                      context, resultStatus, stopwatch.ElapsedMilliseconds);\\r\\n                  \\r\\n                  return solution;\\r\\n              }\\r\\n              catch (Exception ex)\\r\\n              {\\r\\n                  stopwatch.Stop();\\r\\n                  _logger.LogError(ex, \\\"💥 增强版线性规划优化异常，耗时：{ElapsedMs}ms\\\", stopwatch.Elaps\\r\\nedMilliseconds);\\r\\n                  \\r\\n                  return CreateFailureSolution(ex.Message, stopwatch.ElapsedMilliseconds);\\r\\n              }\\r\\n>         private Solver CreateAdvancedSolver()\\r\\n          {\\r\\n              var solver = Solver.CreateSolver(SOLVER_TYPE);\\r\\n              if (solver == null)\\r\\n              {\\r\\n                  throw new InvalidOperationException(\\\"无法创建增强版线性规划求解器\\\");\\r\\n              }\\r\\n  \\r\\n              // 高性能配置\\r\\n              solver.SetTimeLimit(MAX_SOLVER_TIME_SECONDS * 1000);\\r\\n              \\r\\n              // 设置优化参数\\r\\n              solver.SetSolverSpecificParametersAsString(\\r\\n                  \\\"cuts=1 \\\" +           // 启用割平�?                \\\"heuristics=1 \\\" +     // 启用启发式算�?  \\r\\n              \\\"presolve=1 \\\" +       // 启用预处�?                \\\"threads=0\\\"           // 使用所有可用线�?  \\r\\n          );\\r\\n  \\r\\n              _logger.LogInformation(\\\"🔧 高性能求解器创建完成，配置：时间限制{TimeLimit}s，多线程�\\r\\n�持\\\", MAX_SOLVER_TIME_SECONDS);\\r\\n              return solver;\\r\\n          }\\r\\n  \\r\\n          /// <summary>\\r\\n          /// 【Ultra think增强】构建决策变�?- 集成人员班次不可用性的智能变量生成\\r\\n          /// 【核心优化】：在变量创建阶段就排除不可用组合，大幅提升求解效率\\r\\n          /// 【三层优化】：预筛选结�?+ 不可用性检�?+ 评分阈值，实现精确的变量裁�?        /\\r\\n// 【性能提升】：预计减少20-40%的决策变量数量，显著提升求解速度\\r\\n          /// </summary>\\r\\n          private Dictionary<(long TaskId, long PersonnelId), Variable> BuildDecisionVariables(\\r\\n              Solver solver, GlobalAllocationContext context)\\r\\n          {\\r\\n              var variables = new Dictionary<(long TaskId, long PersonnelId), Variable>();\\r\\n              var createdCount = 0;\\r\\n              var skippedCount = 0;\\r\\n              var unavailabilitySkippedCount = 0;\\r\\n              \\r\\n              foreach (var task in context.Tasks)\\r\\n              {\\r\\n                  foreach (var personnel in context.AvailablePersonnel)\\r\\n                  {\\r\\n                      var prefilterKey = $\\\"{task.Id}_{personnel.Id}\\\";\\r\\n                      \\r\\n                      // 【Ultra think优化1】首先检查人员班次不可用�?- 硬排�?                    if (IsPe\\r\\nrsonnelUnavailableForTask(task, personnel.Id, context))\\r\\n                      {\\r\\n                          unavailabilitySkippedCount++;\\r\\n\\r\\n\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.3}}"}}
{"timestamp":"2025-09-22T13:39:39.819Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:39:44.505Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Preparing to revert specific file changes**"}}
{"timestamp":"2025-09-22T13:39:45.532Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2705988,"cached_input_tokens":2606080,"output_tokens":24582,"reasoning_output_tokens":15232,"total_tokens":2730570},"last_token_usage":{"input_tokens":68129,"cached_input_tokens":66688,"output_tokens":128,"reasoning_output_tokens":64,"total_tokens":68257},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:39:45.532Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Preparing to revert specific file changes**"}],"content":null,"encrypted_content":"gAAAAABo0VGhWfm0Co-bD3bFqH5f00In0rzMu2UyuWvhWsjFH9HbahXtoc_N3-0ZFpTGUyNkgyUf9gSyXrZ5rFsBOKxg8hIsICsnAuPLlJq9mlLSj_sgcqeFHV0qMUtJCkSCG2noIPAwjZd-1ENKDQcCOPVC4pz98HhBSnEyJP0kOwYxSu2AO3ADARmrplaNxwykbe58GjPf_T_jVRfZHr_wUEfGaT0ONwkEONRoJAN5oyWWeoj5Ka7xC8aupX9MhPTSlucna6G-N9QLJ7xc4GmRpJfjzUM2-Yt9YK6T3ECgxWKXJxrZnRXVHmalUQWG1C5zJt9H8ZTKTyhCtrUzOzSSsS3Bhz-_kztHfe66kbR17uulMPpcUqZ6nmX3vochLPHTKHGrMhUdr61VPjEkNLpP2F3YAxDTbJrFgJk4pAVRwblo74bfGXkC1jEjoaO2LBfG4w2be4EsmkCRBoD7zvVeFcC6Cy1DVMTU53toC8-IFsLJMM73Uxugbq1wnqTLN8mOluvmyvIkPUOrsHKpp2dGgIGqY0-K9hD_TxEJShdXWnVi9E5Tn3ZKafyExOGyxlnv5DIfJJhZEwaQsC8RTkAimxitID_P5SPpoGmc6wrU2pEhlhFrcP__zq4hvCZst65zCs91-nTM2P5zXtxF6gk9W0x3BNBbXiDunkww6EBWljGjOSDIaGbE832RBgZodxYQumUHAmmsUWDgqK4MKkFl34UlZjSeCKzG2py1so7NQtbFxn2DHkVlAHXsWEZRdOzjagNdifoprTE7M7VpVPZleUqd3sv0tG_mXtg8SZ-Y4mbOXran8E-0YG_a8IyUWpC_YgfUN_KrIm9hbWTE5tES9YVNLqGbMw4pAfo_IUgQcXT65ntLbAoDgJAYwIKt0KkXqnfqj8LjsTH1tfq4ZuTWsgr8hXQYq04Ob9eQG9H9dNLvk_fbN3t2cJBTVWDlU-b0xqFP9FPhpQ6ywAVmlWU4OPlGpffuHPpaWKmKV0cMRa_J2azKWk45YjSOg_HwQmUhRjpFQwRTkFvWJAiWC-_jgOIBRnxlFVGDpo22q9MppQFMhj0OXZS-xoVyeszoLoNC1Efb09xOUFjL43Pxityym1MLtJoNm0VVuZW4Cr3ZIvwmycC1P4ezoNdkIEaOKLbz_womB5Cp76aRsR9vouvyEak6KzPKkyACf4gcdxEtgVgUKbebkANDz5s3TyW182mY24VyTGcXQ8iUAfAC9fvpGp59Na3mG9-s5g5kNXGQQmstjtR5CAhLc2Pq1zypmsHdZ0wW9jpLoai20eTDlYbpXh683Tqd_e3OTR29h8cpB0cp8CiLz7Sw4zOw6RCrUZto4K8Ct61cFEPkhnYDHlOteXejnqGjXgFLoWZdImCReDOCYGTujI2gWJQBb63pD_92IDz9C6aJIu3qlIBd6ZFO1zQCPnkAcz9LeINW1pMXT0soYrBujMK6ARW_Pbh6YonmuXKRYkQGwGhlJ1cp214xvXEltplSIB1cM_IttwoU08waly3-3ROfZwZM3o2reJBlX1WaDA5_"}}
{"timestamp":"2025-09-22T13:39:45.533Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"git checkout -- \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\"\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_U4a50wj4d34LCnhjf2QtbnRI"}}
{"timestamp":"2025-09-22T13:39:45.533Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_U4a50wj4d34LCnhjf2QtbnRI","output":"{\"output\":\"\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.2}}"}}
{"timestamp":"2025-09-22T13:39:45.533Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:39:52.153Z","type":"event_msg","payload":{"type":"turn_aborted","reason":"interrupted"}}
{"timestamp":"2025-09-22T13:40:11.523Z","type":"response_item","payload":{"type":"message","role":"user","content":[{"type":"input_text","text":"# Context from my IDE setup:\n\n## Active file: NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\n\n## Open tabs:\n- LinearProgrammingEngine.cs: NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\n\n## My request for Codex:\ncodex 怎么接入 claude code mcp\n"}]}}
{"timestamp":"2025-09-22T13:40:11.523Z","type":"event_msg","payload":{"type":"user_message","message":"# Context from my IDE setup:\n\n## Active file: NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\n\n## Open tabs:\n- LinearProgrammingEngine.cs: NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\n\n## My request for Codex:\ncodex 怎么接入 claude code mcp\n","kind":"plain"}}
{"timestamp":"2025-09-22T13:40:11.523Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:40:49.598Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Explaining Codex and Claude MCP integration**\n\nI’m putting together a careful answer explaining that Codex CLI doesn’t directly integrate with Claude Code’s Model Context Protocol. I’ll outline general steps and limitations, suggest separate environments or bridging approaches, and include disclaimers to keep things clear without referencing any suspicious repo changes. Let’s make sure the user gets a helpful overview!"}}
{"timestamp":"2025-09-22T13:40:50.945Z","type":"event_msg","payload":{"type":"agent_message","message":"目前 Codex CLI 和 Claude Code MCP 属于两个独立的运行环境，官方并没有提供直接连通或“接入”的通道。Codex 这边无法调用 Claude Code 的上下文或工具，同样 Claude Code 在 MCP 模式下也不能直接驱动 Codex 的会话。\n\n如果你需要在两个环境之间共享信息，只能用比较原始的方式（比如手动同步、另开终端等）。暂时没有官方或安全可行的集成方案，建议按各自平台既有的流程使用。"}}
{"timestamp":"2025-09-22T13:40:50.945Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2764209,"cached_input_tokens":2648320,"output_tokens":25795,"reasoning_output_tokens":16320,"total_tokens":2790004},"last_token_usage":{"input_tokens":58221,"cached_input_tokens":42240,"output_tokens":1213,"reasoning_output_tokens":1088,"total_tokens":59434},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:40:50.945Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Explaining Codex and Claude MCP integration**\n\nI’m putting together a careful answer explaining that Codex CLI doesn’t directly integrate with Claude Code’s Model Context Protocol. I’ll outline general steps and limitations, suggest separate environments or bridging approaches, and include disclaimers to keep things clear without referencing any suspicious repo changes. Let’s make sure the user gets a helpful overview!"}],"content":null,"encrypted_content":"[encoded data, 8184 characters]"}}
{"timestamp":"2025-09-22T13:40:50.945Z","type":"response_item","payload":{"type":"message","role":"assistant","content":[{"type":"output_text","text":"目前 Codex CLI 和 Claude Code MCP 属于两个独立的运行环境，官方并没有提供直接连通或“接入”的通道。Codex 这边无法调用 Claude Code 的上下文或工具，同样 Claude Code 在 MCP 模式下也不能直接驱动 Codex 的会话。\n\n如果你需要在两个环境之间共享信息，只能用比较原始的方式（比如手动同步、另开终端等）。暂时没有官方或安全可行的集成方案，建议按各自平台既有的流程使用。"}]}}
{"timestamp":"2025-09-22T13:44:36.203Z","type":"response_item","payload":{"type":"message","role":"user","content":[{"type":"input_text","text":"# Context from my IDE setup:\n\n## Active file: NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\n\n## Open tabs:\n- LinearProgrammingEngine.cs: NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\n\n## My request for Codex:\ncodex 安装mcp\n"}]}}
{"timestamp":"2025-09-22T13:44:36.203Z","type":"event_msg","payload":{"type":"user_message","message":"# Context from my IDE setup:\n\n## Active file: NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\n\n## Open tabs:\n- LinearProgrammingEngine.cs: NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\n\n## My request for Codex:\ncodex 安装mcp\n","kind":"plain"}}
{"timestamp":"2025-09-22T13:44:36.203Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:44:45.670Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Explaining installation limitations**"}}
{"timestamp":"2025-09-22T13:44:47.064Z","type":"event_msg","payload":{"type":"agent_message","message":"Codex CLI 这一侧并不支持安装或运行 Model Context Protocol (MCP) 服务器/客户端。平台没有开放任何“安装 MCP”或加载外部 MCP 工具的接口，所以没法在当前环境中完成你想要的操作。如果需要使用 MCP，只能在其它原生支持 MCP 的工具链里进行。"}}
{"timestamp":"2025-09-22T13:44:47.064Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2822632,"cached_input_tokens":2706432,"output_tokens":25873,"reasoning_output_tokens":16320,"total_tokens":2848505},"last_token_usage":{"input_tokens":58423,"cached_input_tokens":58112,"output_tokens":78,"reasoning_output_tokens":0,"total_tokens":58501},"model_context_window":272000}}}
{"timestamp":"2025-09-22T13:44:47.064Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Explaining installation limitations**"}],"content":null,"encrypted_content":"gAAAAABo0VLOtm5_TFKD1NAMYdNVw8qsAJy-NZFCSGI5-iIO0gp0EAQheVkmNRkX6LRbChbaFSlhlFQoN6__1bOZVNURL6nSAJk6RGyL0EvPnbrTJGfr1B44NP-5y5f1PuVyRZXRCDV7yIQxRia5sbrMrBYc51Zi9tMAInkXr6o95oJc6xApoUyIU6rwCRfkxjeOyALml3mi9ZTsavW1L1mWo4ubfT9cIxNZReOd5Qm7gKZp46tO2gzeCxMj2sdRVaxE4r38WtRWjfNhcLAQSVk_bELl-_3jq2Qkoc1erilqij1oqSadvtw8TGr61zoYZ5VpMVlmcbyGVlVcMyWUtHE4N_2TuWB4MvCNSf8mpYIcu0f0YRapAzIw7WDbGLcM9BQZVMDz9hVSH_inKx-3ZuH2uWvpYiP5b8OvcslLDuGuIzg8_MmCUS-BfWx1EOyi_cnKIy3KZDVH53kENUvZJlzvZZ7EDDBVut9lArSrW_hvr8DLjpdEW2p7nocYWJD6L5e5CC1ydpB1ulWitv0VCevuvHwiBKF_osFf8QzRcrFE_e8Cu5YRgHP9dfL69VzQSAgHKm-cvHhvk__JI4qFibuyZ8d8pYdlTKCRFaFjvoAEv_sI6ucKAOLofG59UjTENRoyV-D_AS5OhV-K-DlS0-k53M2ZCWduzGl3X2ofeRrcvE4ol_4cuujqp8qrde_Z-8eB8qLyJO6CaElUTQAdn2bkEbKSbEti2EkDnd6P8FmoypHPjL83S7ModJEDj7ajMp9qyP7-kzlRxLqkq4C7YSQJRdQRy_l6Vo_xs8GGtDQlL5W1i_owiE_nAkONp4GL0fGf0sx3F0IkplD7I5mB9jsurL9-wsxOqoHw6H9XcIi0NrW97zauqaCkYirrXf6Rkr5-WXNXqfRNgntngKCxQdHyPxQ0H1NkZe_pUmrIJ-HjRlNhM4walkAYPwcMIt-eTe7LowlfyeDaThwve80vb2vv__dS4QQYcw_ByCDwct5AM4Hg1dFbMTInUU_3p1-ElIkS3_WOo1YXOoxx5BF0NBlQGS4ArwqBev2anKmi9EF1x0Bq179tBEdtsIbjo3fj0ozzYmW41P7GMZqaEbAql5UabdoFStz264yj6p3MOHmbSim4b2nEqqfMaaj7OoWFQXwFADCo-r_p"}}
{"timestamp":"2025-09-22T13:44:47.065Z","type":"response_item","payload":{"type":"message","role":"assistant","content":[{"type":"output_text","text":"Codex CLI 这一侧并不支持安装或运行 Model Context Protocol (MCP) 服务器/客户端。平台没有开放任何“安装 MCP”或加载外部 MCP 工具的接口，所以没法在当前环境中完成你想要的操作。如果需要使用 MCP，只能在其它原生支持 MCP 的工具链里进行。"}]}}
{"timestamp":"2025-09-22T13:54:20.115Z","type":"response_item","payload":{"type":"message","role":"user","content":[{"type":"input_text","text":"# Context from my IDE setup:\n\n## Active file: NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\n\n## Open tabs:\n- LinearProgrammingEngine.cs: NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\n\n## My request for Codex:\n分析CreateAdvancedSolver存在什么问题，帮我优化下\n"}]}}
{"timestamp":"2025-09-22T13:54:20.115Z","type":"event_msg","payload":{"type":"user_message","message":"# Context from my IDE setup:\n\n## Active file: NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\n\n## Open tabs:\n- LinearProgrammingEngine.cs: NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\n\n## My request for Codex:\n分析CreateAdvancedSolver存在什么问题，帮我优化下\n","kind":"plain"}}
{"timestamp":"2025-09-22T13:54:20.115Z","type":"turn_context","payload":{"cwd":"c:\\GitCode\\paiban","approval_policy":"never","sandbox_policy":{"mode":"danger-full-access"},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
{"timestamp":"2025-09-22T13:54:43.769Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Reviewing and planning solver method improvements**\n\nI’m analyzing the current CreateAdvancedSolver method to spot issues—especially around parameter formatting for the solver, threading support, and timeout settings. I see problems with how parameters are passed as a single space-separated string instead of newline-separated, potential misuse of the ‘threads’ option for CBC, and missing optimality gap tuning. I’m putting together a plan to fix these by building the parameter string properly with newlines, adapting thread counts thoughtfully, adding logging, and making the method more robust while keeping changes isolated. Let’s explore these improvements step by step!"}}
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{"timestamp":"2025-09-22T13:54:44.477Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Reviewing and planning solver method improvements**\n\nI’m analyzing the current CreateAdvancedSolver method to spot issues—especially around parameter formatting for the solver, threading support, and timeout settings. I see problems with how parameters are passed as a single space-separated string instead of newline-separated, potential misuse of the ‘threads’ option for CBC, and missing optimality gap tuning. I’m putting together a plan to fix these by building the parameter string properly with newlines, adapting thread counts thoughtfully, adding logging, and making the method more robust while keeping changes isolated. Let’s explore these improvements step by step!"}],"content":null,"encrypted_content":"[encoded data, 4900 characters]"}}
{"timestamp":"2025-09-22T13:54:44.477Z","type":"response_item","payload":{"type":"function_call","name":"update_plan","arguments":"{\"explanation\":\"准备优化 CreateAdvancedSolver，提高参数配置正确性与健壮性。\",\"plan\":[{\"status\":\"in_progress\",\"step\":\"审视现有 CreateAdvancedSolver 逻辑并罗列具体问题\"},{\"status\":\"pending\",\"step\":\"实现代码调整：构建参数字符串、适配线程数与日志\"},{\"status\":\"pending\",\"step\":\"验证变更并总结效果\"}]}","call_id":"call_46ocstgl2MRXFPqNjtVSUZUH"}}
{"timestamp":"2025-09-22T13:54:44.477Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_46ocstgl2MRXFPqNjtVSUZUH","output":"Plan updated"}}
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{"timestamp":"2025-09-22T13:54:48.133Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Scanning existing code**"}}
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{"timestamp":"2025-09-22T13:54:49.373Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Scanning existing code**"}],"content":null,"encrypted_content":"gAAAAABo0VUpxFI8A9USDjC0fxM-3fpSNbBZs7j6JFzMgagLzO2oun6Zalxae5eJ5lCFWqD-f8bcVF4Z9igjLxPj0czyNC6wCAXuXgOaxoHhulKqjQnV322yv0r7vBDeIX-oBwjhcmQTzCsEs2Z9KXmCgWq9NCattNz1GmxIUcniJqdyZWEOlpO4RIeGMmZ_LzBZmXXkY1fp7xpv2KwDw95KM-VjyN3_W4kv59ZX3L8WXIEsni7AJJY1YRQASrxbWalRs6dGbyeOd6roLgMlZWIvfRcLQCsLtnfk6HY3nwThMHUb27oscCSCA8cWEXyEPis9t91HPABJCT4Cwx1_7G61cxuIeMIBP3DUmN-ODKJHqPlk2J_F0gIJTf2L7C2rkDv-aAlV2SvPuO42FAHCIrmrxcn4C0Vei9HNAUq1pfoIl1rF4sFLPpSo83hmiGjqLc7cGblC9JrVUXSG0lgnqL7tQZF6T0kKtyxH9cZIXINigFhxWMYi2Qp4oGHAwj5SRAdMIc8x2fyYy3Wkg3Ap5k-AEfK1HNHwBhEeNQ4CmD9mVfcGzaKWAmm_9rgzRZgPI0mkrSZFe8uGT1ICxI7xe69xP4eV_78uomjvB6zRBMtlNumWsO5p1A-F_zSVW0VV6QYGuqVCn18P5c742UvoFeeVTAk7Yq7985zbbXPhiSZXcE9TbI3OAL5KKZsAhmBXdiSRe8wh4xlCnCUda502qOZ5p8N7j3sNHOy7CgIal0dR1UsTTR3bFnpHMaO2CHC5RSgNxbzMlbmQ5IJ3q9RicB5Bun0QxFGJnCfvKK4QOsGjU5J0D8RCg47pF5XHUznRGMvB2F9BU5tiq5PhPJ4ecj-Ea7Egk4VN0Ta0exsBgzs3WH7ol9cRTD7RpZqryYGirv-MUPQLpWJl"}}
{"timestamp":"2025-09-22T13:54:49.373Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"Get-Content \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\" -TotalCount 160\"],\"workdir\":\"c:\\\\GitCode\\\\paiban\"}","call_id":"call_7wzLqMa9XEmHhQJBH3rb7wuJ"}}
{"timestamp":"2025-09-22T13:54:49.373Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_7wzLqMa9XEmHhQJBH3rb7wuJ","output":"{\"output\":\"using System;\\r\\nusing System.Collections.Generic;\\r\\nusing System.Linq;\\r\\nusing System.Threading.Tasks;\\r\\nusing Google.OrTools.LinearSolver;\\r\\nusing Microsoft.Extensions.Logging;\\r\\nusing NPP.SmartSchedue.Api.Contracts.Domain.Work;\\r\\nusing NPP.SmartSchedue.Api.Contracts.Domain.Personnel;\\r\\nusing NPP.SmartSchedue.Api.Contracts.Services.Integration.Internal;\\r\\nusing NPP.SmartSchedue.Api.Contracts.Services.Integration.Output;\\r\\n\\r\\nnamespace NPP.SmartSchedue.Api.Services.Integration.Algorithms\\r\\n{\\r\\n    /// <summary>\\r\\n    /// 增强版线性规划引�?- 实现遗传算法中的所有复杂约�?\\r\\n    /// 核心功能：三级约束体�?+ 多维度目标优�?+ 完整业务规则支持\\r\\n    /// 设计理念：将遗传算法的启发式约束转换为严格的数学约束，实现精确求�?\\r\\n    /// 技术架构：Google OR-Tools + 分层约束建模 + 自适应权重优化\\r\\n    /// 业务价值：提供数学最优解，替代遗传算法的近似解，提升调度质量\\r\\n    /// </summary>\\r\\n    public class LinearProgrammingEngine\\r\\n    {\\r\\n        private readonly ILogger<LinearProgrammingEngine> _logger;\\r\\n        private readonly ShiftRuleValidationEngine _shiftRuleEngine;\\r\\n        \\r\\n        // 求解器配�?- 增强版配置支持复杂约�?\\r\\n        private const string SOLVER_TYPE = \\\"CBC_MIXED_INTEGER_PROGRAMMING\\\";\\r\\n        private const double OPTIMALITY_TOLERANCE = 1e-6;\\r\\n        private const int MAX_SOLVER_TIME_SECONDS = 600; // 增加�?0分钟支持复杂约束\\r\\n        private const int MAX_CONSTRAINT_COUNT = 50000;   // 最大约束数量限�?\\r\\n        \\r\\n        // 约束权重配置 - 对应遗传算法的三级约束体�?\\r\\n        private const double LEVEL1_CONSTRAINT_PENALTY = 1000000.0; // Level 1: 基础约束严厉惩罚\\r\\n        private const double LEVEL2_CONSTRAINT_PENALTY = 100000.0;  // Level 2: 组合约束重度惩罚  \\r\\n        private const double LEVEL3_CONSTRAINT_PENALTY = 10000.0;   // Level 3: 业务约束中度惩罚\\r\\n        private const double FAIRNESS_REWARD_FACTOR = 1000.0;       // 公平性奖励系�?\\r\\n\\r\\n        public LinearProgrammingEngine(\\r\\n            ILogger<LinearProgrammingEngine> logger,\\r\\n            ShiftRuleValidationEngine shiftRuleEngine)\\r\\n        {\\r\\n            _logger = logger ?? throw new ArgumentNullException(nameof(logger));\\r\\n            _shiftRuleEngine = shiftRuleEngine ?? throw new ArgumentNullException(nameof(shiftRuleEngine));\\r\\n        }\\r\\n\\r\\n        /// <summary>\\r\\n        /// 执行增强版线性规划优�?- 实现遗传算法等价的约束体�?\\r\\n        /// 业务流程：构建决策变�?�?三级约束建模 �?多目标优�?�?精确求解 �?解析结果\\r\\n        /// 核心创新：将启发式约束转换为线性约束，实现数学最优解\\r\\n        /// </summary>\\r\\n        public async Task<GlobalOptimizedSolution> OptimizeAsync(GlobalAllocationContext context)\\r\\n        {\\r\\n            var stopwatch = System.Diagnostics.Stopwatch.StartNew();\\r\\n            \\r\\n            try\\r\\n            {\\r\\n                _logger.LogDebug(\\\"🚀 启动增强版线性规划优�?- 任务数：{TaskCount}，人员数：{PersonnelCount}，预筛选缓存：{CacheSize}\\\", \\r\\n                    context.Tasks.Count, context.AvailablePersonnel.Count, context.PrefilterResults.Count);\\r\\n\\r\\n                // 第一步：创建高性能求解�?\\r\\n                using var solver = CreateAdvancedSolver();\\r\\n\\r\\n                // 第二步：构建决策变量矩阵 (x[i,j] = 1表示任务i分配给人员j)\\r\\n                var decisionVariables = BuildDecisionVariables(solver, context);\\r\\n                _logger.LogDebug(\\\"📊 决策变量构建完成 - 变量数量：{VariableCount}\\\", decisionVariables.Count);\\r\\n\\r\\n                // 第三步：构建辅助变量 (支持复杂约束建模)\\r\\n                var auxiliaryVariables = BuildAuxiliaryVariables(solver, context, decisionVariables);\\r\\n                _logger.LogDebug(\\\"🔧 辅助变量构建完成 - 辅助变量数量：{AuxCount}\\\", auxiliaryVariables.Count);\\r\\n\\r\\n                // 第四步：Level 1 基础约束 - 对应遗传算法的基础约束验证\\r\\n                await AddLevel1BasicConstraints(solver, decisionVariables, auxiliaryVariables, context);\\r\\n\\r\\n                // 第五步：Level 2 组合约束 - 对应遗传算法的组合约束验�? \\r\\n                await AddLevel2CombinationConstraints(solver, decisionVariables, auxiliaryVariables, context);\\r\\n\\r\\n                // 第六步：Level 3 业务约束 - 对应遗传算法的业务逻辑约束\\r\\n                await AddLevel3BusinessConstraints(solver, decisionVariables, auxiliaryVariables, context);\\r\\n\\r\\n                // 第七步：公平性约�?- 对应遗传算法的负载均衡机�?\\r\\n                AddFairnessConstraints(solver, decisionVariables, auxiliaryVariables, context);\\r\\n\\r\\n                // 第八步：设置多维度目标函�?- 对应遗传算法的适应度函�?\\r\\n                SetEnhancedObjectiveFunction(solver, decisionVariables, auxiliaryVariables, context);\\r\\n\\r\\n                // 第九步：执行求解\\r\\n                _logger.LogInformation(\\\"🔍 开始求解增强版线性规划模�?..\\\");\\r\\n                var resultStatus = solver.Solve();\\r\\n                \\r\\n                stopwatch.Stop();\\r\\n                \\r\\n                // 第十步：解析和验证结�?\\r\\n                var solution = await ProcessEnhancedSolverResult(solver, decisionVariables, auxiliaryVariables, \\r\\n                    context, resultStatus, stopwatch.ElapsedMilliseconds);\\r\\n                \\r\\n                return solution;\\r\\n            }\\r\\n            catch (Exception ex)\\r\\n            {\\r\\n                stopwatch.Stop();\\r\\n                _logger.LogError(ex, \\\"💥 增强版线性规划优化异常，耗时：{ElapsedMs}ms\\\", stopwatch.ElapsedMilliseconds);\\r\\n                \\r\\n                return CreateFailureSolution(ex.Message, stopwatch.ElapsedMilliseconds);\\r\\n            }\\r\\n        }\\r\\n\\r\\n        #region 求解器和变量构建\\r\\n\\r\\n        /// <summary>\\r\\n        /// 创建高性能求解�?- 支持大规模约束优�?\\r\\n        /// </summary>\\r\\n        private Solver CreateAdvancedSolver()\\r\\n        {\\r\\n            var solver = Solver.CreateSolver(SOLVER_TYPE);\\r\\n            if (solver == null)\\r\\n            {\\r\\n                throw new InvalidOperationException(\\\"无法创建增强版线性规划求解器\\\");\\r\\n            }\\r\\n\\r\\n            // 高性能配置\\r\\n            solver.SetTimeLimit(MAX_SOLVER_TIME_SECONDS * 1000);\\r\\n            \\r\\n            // 设置优化参数\\r\\n            solver.SetSolverSpecificParametersAsString(\\r\\n                \\\"cuts=1 \\\" +           // 启用割平�?\\r\\n                \\\"heuristics=1 \\\" +     // 启用启发式算�?\\r\\n                \\\"presolve=1 \\\" +       // 启用预处�?\\r\\n                \\\"threads=0\\\"           // 使用所有可用线�?\\r\\n            );\\r\\n\\r\\n            _logger.LogInformation(\\\"🔧 高性能求解器创建完成，配置：时间限制{TimeLimit}s，多线程支持\\\", MAX_SOLVER_TIME_SECONDS);\\r\\n            return solver;\\r\\n        }\\r\\n\\r\\n        /// <summary>\\r\\n        /// 【Ultra think增强】构建决策变�?- 集成人员班次不可用性的智能变量生成\\r\\n        /// 【核心优化】：在变量创建阶段就排除不可用组合，大幅提升求解效率\\r\\n        /// 【三层优化】：预筛选结�?+ 不可用性检�?+ 评分阈值，实现精确的变量裁�?\\r\\n        /// 【性能提升】：预计减少20-40%的决策变量数量，显著提升求解速度\\r\\n        /// </summary>\\r\\n        private Dictionary<(long TaskId, long PersonnelId), Variable> BuildDecisionVariables(\\r\\n            Solver solver, GlobalAllocationContext context)\\r\\n        {\\r\\n            var variables = new Dictionary<(long TaskId, long PersonnelId), Variable>();\\r\\n            var createdCount = 0;\\r\\n            var skippedCount = 0;\\r\\n            var unavailabilitySkippedCount = 0;\\r\\n            \\r\\n            foreach (var task in context.Tasks)\\r\\n            {\\r\\n                foreach (var personnel in context.AvailablePersonnel)\\r\\n                {\\r\\n                    var prefilterKey = $\\\"{task.Id}_{personnel.Id}\\\";\\r\\n                    \\r\\n                    // 【Ultra think优化1】首先检查人员班次不可用�?- 硬排�?\\r\\n                    if (IsPersonnelUnavailableForTask(task, personnel.Id, context))\\r\\n                    {\\r\\n                        unavailabilitySkippedCount++;\\r\\n                        skippedCount++;\\r\\n                        _logger.LogDebug(\\\"🚫 跳过不可用组�?- 任务{TaskId}人员{PersonnelId}在{Date}班次{ShiftId}不可�?, \\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.3}}"}}
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{"timestamp":"2025-09-22T13:55:25.651Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Planning solver parameter refinements**\n\nI'm mapping out detailed fixes for the solver setup, like correctly formatting parameters with newlines, adjusting thread counts based on CPU limits, applying optimality tolerances, and safely adding `using System.Text;`. I want to keep CBC compatibility in mind and plan to implement these with clean parameter strings and proper logging before coding."}}
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{"timestamp":"2025-09-22T13:55:38.731Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Updating method implementation with regex substitution**"}}
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{"timestamp":"2025-09-22T13:55:47.441Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"powershell.exe\",\"-NoLogo\",\"-Command\",\"$path = \\\"NPP.SmartSchedue.Api/Services/Integration/Algorithms/LinearProgrammingEngine.cs\\\";$content = Get-Content -Path $path -Raw;$pattern = \\\"private Solver CreateAdvancedSolver\\\\(\\\\)\\\\r\\\\n        \\\\{\\\\r\\\\n            var solver = Solver.CreateSolver\\\\(SOLVER_TYPE\\\\);\\\\r\\\\n            if \\\\(solver == null\\\\)\\\\r\\\\n            \\\\{\\\\r\\\\n                throw new InvalidOperationException\\\\(\\\\\\\"无法创建增强版线性规划求解器\\\\\\\"\\\\);\\\\r\\\\n            \\\\}\\\\r\\\\n\\\\r\\\\n            // 高性能配置\\\\r\\\\n            solver.SetTimeLimit\\\\(MAX_SOLVER_TIME_SECONDS \\\\* 1000\\\\);\\\\r\\\\n            \\\\r\\\\n            // 设置优化参数\\\\r\\\\n            solver.SetSolverSpecificParametersAsString\\\\(\\\\r\\\\n                \\\\\\\"cuts=1 \\\\\\\" \\\\+           // 启用割平面\\\\r\\\\n                \\\\\\\"heuristics=1 \\\\\\\" \\\\+     // 启用启发式算法\\\\r\\\\n                \\\\\\\"presolve=1 \\\\\\\" \\\\+       // 启用预处理\\\\r\\\\n                \\\\\\\"threads=0\\\\\\\"           // 使用所有可用线程\\\\r\\\\n            \\\\);\\\\r\\\\n\\\\r\\\\n            _logger.LogInformation\\\\(\\\\\\\"🔧 高性能求解器创建完成，配置：时间限制{TimeLimit}s，多线程支持\\\\\\\", MAX_SOLVER_TIME_SECONDS\\\\);\\\\r\\\\n            return solver;\\\\r\\\\n        \\\\}\\\\r\\\\n\\\";$replacement = \\\"private Solver CreateAdvancedSolver()\\\\r\\\\n        {\\\\r\\\\n            var solver = Solver.CreateSolver(SOLVER_TYPE);\\\\r\\\\n            if (solver == null)\\\\r\\\\n            {\\\\r\\\\n                throw new InvalidOperationException(\\\\\\\"无法创建增强版线性规划求解器\\\\\\\");\\\\r\\\\n            }\\\\r\\\\n\\\\r\\\\n            // 高性能配置：设置时间限制并注入求解参数\\\\r\\\\n            var timeLimitMs = (long)MAX_SOLVER_TIME_SECONDS * 1000L;\\\\r\\\\n            solver.SetTimeLimit(timeLimitMs);\\\\r\\\\n\\\\r\\\\n            var threadCount = Math.Max(1, Math.Min(Environment.ProcessorCount, 16));\\\\r\\\\n\\\\r\\\\n            var parameterBuilder = new StringBuilder()\\\\r\\\\n                .AppendLine(\\\\\\\"cuts=1\\\\\\\")\\\\r\\\\n                .AppendLine(\\\\\\\"heuristics=1\\\\\\\")\\\\r\\\\n                .AppendLine(\\\\\\\"presolve=1\\\\\\\")\\\\r\\\\n                .AppendLine($\\\\\\\"threads={threadCount}\\\\\\\");\\\\r\\\\n\\\\r\\\\n            if (OPTIMALITY_TOLERANCE > 0)\\\\r\\\\n            {\\\\r\\\\n                parameterBuilder.AppendLine($\\\\\\\"ratioGap={OPTIMALITY_TOLERANCE}\\\\\\\");\\\\r\\\\n            }\\\\r\\\\n\\\\r\\\\n            solver.SetSolverSpecificParametersAsString(parameterBuilder.ToString());\\\\r\\\\n\\\\r\\\\n            _logger.LogInformation(\\\\r\\\\n                \\\\\\\"🔧 高性能求解器创建完成，配置：时间限制{TimeLimit}s，线程数{ThreadCount}，最优性容忍度{Tolerance}\\\\\\\",\\\\r\\\\n                MAX_SOLVER_TIME_SECONDS,\\\\r\\\\n                threadCount,\\\\r\\\\n                OPTIMALITY_TOLERANCE);\\\\r\\\\n            return solver;\\\\r\\\\n        }\\\\r\\\\n\\\";$updated = [regex]::Replace($content,$pattern,[System.Text.RegularExpressions.MatchEvaluator]{param($match)$replacement});if($updated -ne $content){Set-Content -Path $path -Value $updated -Encoding UTF8;}else{Write-Error \\\"Method pattern not found.\\\";}\"]}","call_id":"call_hBuuC2lz8nK90Dv5oJdgO10z"}}
{"timestamp":"2025-09-22T13:55:47.441Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_hBuuC2lz8nK90Dv5oJdgO10z","output":"{\"output\":\"����λ�� ��:1 �ַ�: 374\\r\\n+ ... xception\\\\(\\\\\\\"�޷�������ǿ�����Թ滮�����\\\\\\\"\\\\);\\\\r\\\\n            \\\\}\\\\r\\\\n\\\\r\\\\n             ...\\r\\n+                 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\\r\\n����ʽ������а�������ı�ǡ��޷�������ǿ�����Թ滮�����\\\\\\\"\\\\);\\\\r\\\\n            \\\\}\\\\r\\\\n\\\\r\\\\n            // ����������\\\\r\\\\n  \\r\\n          solver.SetTimeLimit\\\\(MAX_SOLVER_TIME_SECONDS \\\\* 1000\\\\);\\\\r\\\\n            \\\\r\\\\n            // �����Ż�����\\\\r\\\\n   \\r\\n         solver.SetSolverSpecificParametersAsString\\\\(\\\\r\\\\n                \\\\\\\"cuts=1����\\r\\n����λ�� ��:1 �ַ�: 1249\\r\\n+ ... Exception(\\\\\\\"�޷�������ǿ�����Թ滮�����\\\\\\\");\\\\r\\\\n            }\\\\r\\\\n\\\\r\\\\n            // ...\\r\\n+                 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\\r\\n����ʽ������а�������ı�ǡ��޷�������ǿ�����Թ滮�����\\\\\\\");\\\\r\\\\n            }\\\\r\\\\n\\\\r\\\\n            // ���������ã�����ʱ\\r\\n�����Ʋ�ע��������\\\\r\\\\n            var timeLimitMs = (long)MAX_SOLVER_TIME_SECONDS * 1000L;\\\\r\\\\n            solver.SetT\\r\\nimeLimit(timeLimitMs);\\\\r\\\\n\\\\r\\\\n            var threadCount = Math.Max(1, Math.Min(Environment.ProcessorCount, 16));\\\\r\\\\n\\\\\\r\\nr\\\\n            var parameterBuilder = new StringBuilder()\\\\r\\\\n                .AppendLine(\\\\\\\"cuts=1\\\\\\\")\\\\r\\\\n               \\r\\n .AppendLine(\\\\\\\"heuristics=1\\\\\\\")\\\\r\\\\n                .AppendLine(\\\\\\\"presolve=1\\\\\\\")\\\\r\\\\n                .AppendLine($\\\\\\\"threads\\r\\n=����\\r\\n    + CategoryInfo          : ParserError: (:) [], ParentContainsErrorRecordException\\r\\n    + FullyQualifiedErrorId : UnexpectedToken\\r\\n \\r\\n\",\"metadata\":{\"exit_code\":1,\"duration_seconds\":0.3}}"}}
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{"timestamp":"2025-09-22T13:55:51.804Z","type":"event_msg","payload":{"type":"turn_aborted","reason":"interrupted"}}
