38 lines
69 KiB
JSON
38 lines
69 KiB
JSON
{"timestamp":"2025-09-22T16:09:08.127Z","type":"session_meta","payload":{"id":"0199722f-9ea4-7430-b35a-1c9f0a08838a","timestamp":"2025-09-22T16:09:07.492Z","cwd":"C:\\GitCode\\paiban","originator":"codex_cli_rs","cli_version":"0.39.0","instructions":"## 开发规则\r\n\r\n你是一名经验丰富的[专业领域，例如：软件开发工程师 / 系统设计师 / 代码架构师]，专注于构建[核心特长，例如：高性能 / 可维护 / 健壮 / 领域驱动]的解决方案。\r\n\r\n你的任务是：**审查、理解并迭代式地改进/推进一个[项目类型，例如：现有代码库 / 软件项目 / 技术流程]。**\r\n\r\n在整个工作流程中，你必须内化并严格遵循以下核心编程原则，确保你的每次输出和建议都体现这些理念：\r\n\r\n- **简单至上 (KISS):** 追求代码和设计的极致简洁与直观，避免不必要的复杂性。\r\n- **精益求精 (YAGNI):** 仅实现当前明确所需的功能，抵制过度设计和不必要的未来特性预留。\r\n- **坚实基础 (SOLID):**\r\n - **S (单一职责):** 各组件、类、函数只承担一项明确职责。\r\n - **O (开放/封闭):** 功能扩展无需修改现有代码。\r\n - **L (里氏替换):** 子类型可无缝替换其基类型。\r\n - **I (接口隔离):** 接口应专一，避免“胖接口”。\r\n - **D (依赖倒置):** 依赖抽象而非具体实现。\r\n- **杜绝重复 (DRY):** 识别并消除代码或逻辑中的重复模式，提升复用性。\r\n\r\n**请严格遵循以下工作流程和输出要求：**\r\n\r\n1. **深入理解与初步分析（理解阶段）：**\r\n\r\n - 详细审阅提供的[资料/代码/项目描述]，全面掌握其当前架构、核心组件、业务逻辑及痛点。\r\n - 在理解的基础上，初步识别项目中潜在的**KISS, YAGNI, DRY, SOLID**原则应用点或违背现象。\r\n\r\n2. **明确目标与迭代规划（规划阶段）：**\r\n\r\n - 基于用户需求和对现有项目的理解，清晰定义本次迭代的具体任务范围和可衡量的预期成果。\r\n - 在规划解决方案时，优先考虑如何通过应用上述原则，实现更简洁、高效和可扩展的改进，而非盲目增加功能。\r\n\r\n3. **分步实施与具体改进（执行阶段）：**\r\n\r\n - 详细说明你的改进方案，并将其拆解为逻辑清晰、可操作的步骤。\r\n - 针对每个步骤，具体阐述你将如何操作，以及这些操作如何体现**KISS, YAGNI, DRY, SOLID**原则。例如：\r\n - “将此模块拆分为更小的服务，以遵循 SRP 和 OCP。”\r\n - “为避免 DRY，将重复的 XXX 逻辑抽象为通用函数。”\r\n - “简化了 Y 功能的用户流，体现 KISS 原则。”\r\n - “移除了 Z 冗余设计，遵循 YAGNI 原则。”\r\n - 重点关注[项目类型，例如：代码质量优化 / 架构重构 / 功能增强 / 用户体验提升 / 性能调优 / 可维护性改善 / Bug 修复]的具体实现细节。\r\n\r\n4. **总结、反思与展望（汇报阶段）：**\r\n - 提供一个清晰、结构化且包含**实际代码/设计变动建议（如果适用）**的总结报告。\r\n - 报告中必须包含：\r\n - **本次迭代已完成的核心任务**及其具体成果。\r\n - **本次迭代中，你如何具体应用了** **KISS, YAGNI, DRY, SOLID** **原则**，并简要说明其带来的好处（例如，代码量减少、可读性提高、扩展性增强）。\r\n - **遇到的挑战**以及如何克服。\r\n - **下一步的明确计划和建议。**\r\n\r\n---\r\n\r\n### 编码输出/语言偏好###\r\n## Communication & Language\r\n- Default language: Simplified Chinese for issues, PRs, and assistant replies, unless a thread explicitly requests English.\r\n- Keep code identifiers, CLI commands, logs, and error messages in their original language; add concise Chinese explanations when helpful.\r\n- To switch languages, state it clearly in the conversation or PR description.\r\n\r\n## File Encoding\r\nWhen modifying or adding any code files, the following coding requirements must be adhered to:\r\n- Encoding should be unified to UTF-8 (without BOM). It is strictly prohibited to use other local encodings such as GBK/ANSI, and it is strictly prohibited to submit content containing unreadable characters.\r\n- When modifying or adding files, be sure to save them in UTF-8 format; if you find any files that are not in UTF-8 format before submitting, please convert them to UTF-8 before submitting.\n\n--- project-doc ---\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","git":{"commit_hash":"2b3f9acdce96bfa8be7e2cdb15dd399be53e969d","branch":"master","repository_url":"https://git.comzg.com/WuXi/paiban.git"}}}
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{"timestamp":"2025-09-22T16:09:09.375Z","type":"response_item","payload":{"type":"message","role":"user","content":[{"type":"input_text","text":"<user_instructions>\n\n## 开发规则\r\n\r\n你是一名经验丰富的[专业领域，例如：软件开发工程师 / 系统设计师 / 代码架构师]，专注于构建[核心特长，例如：高性能 / 可维护 / 健壮 / 领域驱动]的解决方案。\r\n\r\n你的任务是：**审查、理解并迭代式地改进/推进一个[项目类型，例如：现有代码库 / 软件项目 / 技术流程]。**\r\n\r\n在整个工作流程中，你必须内化并严格遵循以下核心编程原则，确保你的每次输出和建议都体现这些理念：\r\n\r\n- **简单至上 (KISS):** 追求代码和设计的极致简洁与直观，避免不必要的复杂性。\r\n- **精益求精 (YAGNI):** 仅实现当前明确所需的功能，抵制过度设计和不必要的未来特性预留。\r\n- **坚实基础 (SOLID):**\r\n - **S (单一职责):** 各组件、类、函数只承担一项明确职责。\r\n - **O (开放/封闭):** 功能扩展无需修改现有代码。\r\n - **L (里氏替换):** 子类型可无缝替换其基类型。\r\n - **I (接口隔离):** 接口应专一，避免“胖接口”。\r\n - **D (依赖倒置):** 依赖抽象而非具体实现。\r\n- **杜绝重复 (DRY):** 识别并消除代码或逻辑中的重复模式，提升复用性。\r\n\r\n**请严格遵循以下工作流程和输出要求：**\r\n\r\n1. **深入理解与初步分析（理解阶段）：**\r\n\r\n - 详细审阅提供的[资料/代码/项目描述]，全面掌握其当前架构、核心组件、业务逻辑及痛点。\r\n - 在理解的基础上，初步识别项目中潜在的**KISS, YAGNI, DRY, SOLID**原则应用点或违背现象。\r\n\r\n2. **明确目标与迭代规划（规划阶段）：**\r\n\r\n - 基于用户需求和对现有项目的理解，清晰定义本次迭代的具体任务范围和可衡量的预期成果。\r\n - 在规划解决方案时，优先考虑如何通过应用上述原则，实现更简洁、高效和可扩展的改进，而非盲目增加功能。\r\n\r\n3. **分步实施与具体改进（执行阶段）：**\r\n\r\n - 详细说明你的改进方案，并将其拆解为逻辑清晰、可操作的步骤。\r\n - 针对每个步骤，具体阐述你将如何操作，以及这些操作如何体现**KISS, YAGNI, DRY, SOLID**原则。例如：\r\n - “将此模块拆分为更小的服务，以遵循 SRP 和 OCP。”\r\n - “为避免 DRY，将重复的 XXX 逻辑抽象为通用函数。”\r\n - “简化了 Y 功能的用户流，体现 KISS 原则。”\r\n - “移除了 Z 冗余设计，遵循 YAGNI 原则。”\r\n - 重点关注[项目类型，例如：代码质量优化 / 架构重构 / 功能增强 / 用户体验提升 / 性能调优 / 可维护性改善 / Bug 修复]的具体实现细节。\r\n\r\n4. **总结、反思与展望（汇报阶段）：**\r\n - 提供一个清晰、结构化且包含**实际代码/设计变动建议（如果适用）**的总结报告。\r\n - 报告中必须包含：\r\n - **本次迭代已完成的核心任务**及其具体成果。\r\n - **本次迭代中，你如何具体应用了** **KISS, YAGNI, DRY, SOLID** **原则**，并简要说明其带来的好处（例如，代码量减少、可读性提高、扩展性增强）。\r\n - **遇到的挑战**以及如何克服。\r\n - **下一步的明确计划和建议。**\r\n\r\n---\r\n\r\n### 编码输出/语言偏好###\r\n## Communication & Language\r\n- Default language: Simplified Chinese for issues, PRs, and assistant replies, unless a thread explicitly requests English.\r\n- Keep code identifiers, CLI commands, logs, and error messages in their original language; add concise Chinese explanations when helpful.\r\n- To switch languages, state it clearly in the conversation or PR description.\r\n\r\n## File Encoding\r\nWhen modifying or adding any code files, the following coding requirements must be adhered to:\r\n- Encoding should be unified to UTF-8 (without BOM). It is strictly prohibited to use other local encodings such as GBK/ANSI, and it is strictly prohibited to submit content containing unreadable characters.\r\n- When modifying or adding files, be sure to save them in UTF-8 format; if you find any files that are not in UTF-8 format before submitting, please convert them to UTF-8 before submitting.\n\n--- project-doc ---\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>"}]}}
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{"timestamp":"2025-09-22T16:09:09.376Z","type":"response_item","payload":{"type":"message","role":"user","content":[{"type":"input_text","text":"<environment_context>\n <cwd>C:\\GitCode\\paiban</cwd>\n <approval_policy>on-request</approval_policy>\n <sandbox_mode>workspace-write</sandbox_mode>\n <network_access>restricted</network_access>\n <shell>pwsh.exe</shell>\n</environment_context>"}]}}
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{"timestamp":"2025-09-22T16:09:26.388Z","type":"response_item","payload":{"type":"message","role":"user","content":[{"type":"input_text","text":"分析 CreateAdvancedSolver"}]}}
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{"timestamp":"2025-09-22T16:09:26.388Z","type":"event_msg","payload":{"type":"user_message","message":"分析 CreateAdvancedSolver","kind":"plain"}}
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{"timestamp":"2025-09-22T16:09:26.388Z","type":"turn_context","payload":{"cwd":"C:\\GitCode\\paiban","approval_policy":"on-request","sandbox_policy":{"mode":"workspace-write","network_access":false,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
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{"timestamp":"2025-09-22T16:09:36.904Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Preparing to locate CreateAdvancedSolver**"}}
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{"timestamp":"2025-09-22T16:09:41.670Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":4447,"cached_input_tokens":2560,"output_tokens":433,"reasoning_output_tokens":384,"total_tokens":4880},"last_token_usage":{"input_tokens":4447,"cached_input_tokens":2560,"output_tokens":433,"reasoning_output_tokens":384,"total_tokens":4880},"model_context_window":272000}}}
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{"timestamp":"2025-09-22T16:09:41.671Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Preparing to locate CreateAdvancedSolver**"}],"content":null,"encrypted_content":"gAAAAABo0XTB9BQro9OKB5OYTKRk5hOkLJCp0bXm7C0EBdDpH0tsU-0YE11sta9puzlbtHyKgunt8pymvGEXJY7dOkFx2O-ZcoKPJLuPlR2SQ0Zr11isqrZoMnFk4monOM_Obp6Psj79E6RVwHNBWgj-yQUAzepvnIEJha9qLLIbCbVYPaNM-KuPxSGQ7KNwUTHMlaRJ1E8iWumeHIUgu60CE_kn9ZpRrv7k18xB3sxlEix8npsE2nkGzGtcrSAjXsoAJr4vOUJyAw53BAVO1VG9kcDHuhEapByCYP0VCH5z6HCf6iH0Q96D04gWcnF3NKBAswP4tf7XgvIROAzLv8Jq60xN4T63wcHsNeV0CDYQ31clUncPOCF_iQgBjdKJbJsl0TS0D8X6KICupL5Lb8Kb2vca15eBDL4omMPcVf3depd3LM6rhQBx5kg7R10CjnmUgMb47pAlGYN099M-dQMPLSzAzX0T3FJlTUKUOQ6oPDuQvrFtTPJ9kbQibhzXo-MfIOrgKR-q8kqdjMU9KkvwBmZZjSN8g_s9EC3vmitsYJHwW-oTU0UTImGRst19M8QGrV6VQHoleCQBtbuhAT8r41dA9BDc5-8qFrqTpi3EFP4JvUxGOcqbmRpfpFSfGUKl15Kx_KFEqGDyTyjaOm0d1T0B6HTVZPvRCsaGHEVM1uVkUfLee-KmBp--ldTNO54I7R1JfsrxhkUXc9Exahahc-El1vyOHnC00WsmGfaYW_ZdWdLxMj0RikyfPrLmRk-Xr0SDBKPD8Y1EPrS_s2a7mEz2e7tdcEZAjIeLee5ychJchE5GMSfKsqKvqQMdQtQHq5IV5lcFD8J5vU-A49U6MR8PbSyTXvWMftzYGtjKFiH7bumjhLc2NLXSCxaAdjTx9FyC-3irg_e0wmW1f7YsyrhI_v2b9IoUbfdQf4yOHsa8V3f3H3Y7KzfDRepow5ebsbCta_MpMsq6XE5kUqxhR3lpdRItYA_6W-ctTSzBP3f7gYbLS53cYGPklHUixsEp-169JDUR4_QYVH91txjmN9A0FnKiFItxXNf3HOgM7W34-Jg_PnK5hWEnATczJ9Xrykvq13Uzudtm0jFa8IyeZmti54OE2p3pfCWAhLqtN7ycT0m-Dl6MyUmig4VqlpH4rAErFRfWvTrrwbBPCgSzNW7dhYG2KvrjpTN8LVptpf2_2pLol4v-U34W7tsWfWj_UonJfQm6rM5HMSIKo4l2miNEOAHW9wxmG_um9bQBpp59pbgOfGtktKPWefDWLFeouZfOa3zYGbw87M81QR7fc4byyUpBmCz95_JUCF0Yug6yeZsM9HBmuqRnpPUoF8wCHAcbiX3qhjAqFnyp84wylBu5QkFWYU7bfaUZAIjIP0LACUsio3wsn4dlgrSs92AjbrJ6kBSoC8esYhm_1um4_2-JTSh9O4e97vpDolt3X4jmTFbiGfnoI7IyfgA4xQMmP5jr3IycP22H3xSlXHWXHXdUCP1HIlYOOV57hdsqmLO7FLMSEgMjsRZSaIEtwtRybJF5AOvBwHs0ehnbFxJulQW59Rt_EfEzaiyrmryI_QCvVCc-M421lauq-103hx2kBpsi_Q3ZHUddMJjhD7NmVwXlyXL9iJ4244tUfoIotLF-8oLesvtORPiG0ET5d7ZhT5gE1ufmqvVdpJj9pwWDCH4CJ2AsnYZUvQNBMaYyYlkwC19qCw6FXLQnud81Zw9wIBw44ptHuFRBDw7dlW9dTuFensKYmOTZkvFiUQHUu5Qt-g_tmJkhMyqR-qW9MM0ZQpcJhLZeDysplfvk2aB8izgzxYlzIJLGkM6dtwnqxoQhClRYJsR8WbPjWHeGk2HURK9KSq9hirbfEI6fBB6njkg_UmDjnexICu1YNWGO3gV6cLnNDrfByPrzHVjrZ1p7yWSWevgQfmTeJK1cHTTIZwqyb_SrULJpcJPieFGNk3nssdHzu5DkThcfyzkZ1rastx4qdagd8R4vZ2a3Xn7D1eYKcxR0j6D1lE0e8N8n1iL30SAyjeGldj37cyBXI-mVERP6Fnqq8zCJxu0Ji3HIEZlnCkKgFxiGjuPPSeS97d042c9cO5CValI-2L2g3AHvggmEw2wPYw4Q54S3tWuzMJTZc7NOKEX3BBC3pP2yeqxA1-FaaiJl0in-wTUaCW9mFPxoNqQFw2q7rPnD3WZqFGR56Rw0MtYx_BOv4QH4XgDVE98AOJMohAT1XLhBvyN1KX2SOalMaWEIHjA3QF9J1Pb_bPTRD-JfLYJmdmPv5YDi9Tqd1YW_ahC0KclK8SyIlsxqpcVX6f6r6E5Plxf6L3Ggl5EK5hpgz0W00K6O9CFow44COyO3auT516E3cdI7-8T38x4qsD43xjyIq8q4D7Pb54XxIAE8xRyIYscynXmiP0ZjcrPqH6HHIMLtGwdOIMuQVnuJ99xWA5kpa71JzqFF5V3BOZTOK8dhn7okXiJc1tikiwFx-w1i2wAzsNeJRu8_FYMp25aidliGlAIVLTrnxb2_rqFILArdpHywoBiqRBOO4kCwHfp73FHhF5b96aZzqXESgJb9tG09Q7El0HxwHTRftcgdzU2JF5CRqrp-Jc8Oo33xPeeQxDVRiX0qt9ylkl0yP5m6yaxZE_GhYSK9ZACaDJC4l3oKEncY311yAmn4LPTIv_PlEpoH9I4SrYX3GqL6e3elPGUiY18MGrzh8yrs0_PG_TXn2SsdjHGeEVzFWwSwjoAYBmgLdK4G2xvBgXltp1chSJPD30-wXqvETYs7OhcG26gEaSpfIXEz5gcQilJQ7AqSn4cHqpgSJTzq5GcIxtmisSrFnATtzA5HujgYCj9U4zvdUGpx44DCZMvu0PiOUOMvhdH0B6eFBvjH7Py_mvZDYCcQjOkYxtJbvho4DCjqbEIU9SMp_5q3n-Io-9r1lo09QQk9ipVUpd50iuO_Ycl9V4STF0zukFr6YjYcAkjg0Hc1Klq-C3J1vEgmAO4CE7uzxFf9rHJUrbRF03S3YecuPYssSfj1nk4Kxk7ZOjEuKKMHk0o6recapc7Epf2UWDT7WtkdcPOxY-18bg46amr40gxiQ2MtcrpN2H4sz-q7jAahPtcgQKUtFjLYYWuD3Zq2ZXMX6fSf09F2a-gE2Mle6-5fAmiS8wL90fNmg8CT2lMi6tb0Wq6_cWd-pqG5BUHLHWRvuNLiaPLGaZIMBtAZZbxQ15MOJbxIqwQbOrn6r24m7EglnLrt8epiQiuDLRMzR0MuWHeCn2CaG9xffeWOWpveyNYSsEuPcq1--KFJGn5zvqpGznxfAoWpdxk2hwq9ficvQA0yHvCt1pCMG_Dv20bXL-px7JqinxJ4lUKpxNRoFSU0qwBtWnJ9JzufSzc0wWoo1de8YKhwhfZnFqfJHlZjeYc-G_WNUcXoAqIR3O_6SHDjbtjiZ2k4eSQ8yA6Ze0237tSo_ud5Fv42xdPLMN4pfXrFTW0c9k6c61Gvs8nzWmSGr3OjTT2RDM4="}}
|
||
{"timestamp":"2025-09-22T16:09:41.671Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"pwsh.exe\",\"-NoLogo\",\"-Command\",\"rg \\\"CreateAdvancedSolver\\\" -n\"],\"workdir\":\"C:\\\\GitCode\\\\paiban\"}","call_id":"call_b4OX52ECjiZTmTejRblq3DHl"}}
|
||
{"timestamp":"2025-09-22T16:09:41.671Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_b4OX52ECjiZTmTejRblq3DHl","output":"{\"output\":\"NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:61: using var solver = CreateAdvancedSolver();\\r\\nNPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:112: private Solver CreateAdvancedSolver()\\r\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":1.1}}"}}
|
||
{"timestamp":"2025-09-22T16:09:41.671Z","type":"turn_context","payload":{"cwd":"C:\\GitCode\\paiban","approval_policy":"on-request","sandbox_policy":{"mode":"workspace-write","network_access":false,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
|
||
{"timestamp":"2025-09-22T16:09:43.105Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Checking file contents**"}}
|
||
{"timestamp":"2025-09-22T16:09:46.562Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":9473,"cached_input_tokens":5120,"output_tokens":499,"reasoning_output_tokens":384,"total_tokens":9972},"last_token_usage":{"input_tokens":5026,"cached_input_tokens":2560,"output_tokens":66,"reasoning_output_tokens":0,"total_tokens":5092},"model_context_window":272000}}}
|
||
{"timestamp":"2025-09-22T16:09:46.562Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Checking file contents**"}],"content":null,"encrypted_content":"gAAAAABo0XTHGf_ZlGJe8EIcI7ClVqDoEVdl9u0cBX36WmBYuIL-A-odg9cWNkNIKKKg_3qatYnyrgCnce0ch8TVkHNIPLACrt1J9NqKuhYTljZX-hkiYC7HahxW6JPNtyXMUMTFHth5cAlD8gkQvvJFyvZBZRgOQxi63fGKmade6wvp5wjNdf6BH1yYv52QE0wzF8puyMM5eMqK6v5nA6_tobVDgiquLY3nWA_88Hl5xyy-4-FO89NnI4VICh3LLZ2dTZWhsKPKR_UEIU4WwVKI0gyQG6HautrQsxoq1tLC6ThA9AwXzFs8ytTTK4jSNZlmNxFErV3ELOuBdYeOAMuFgdq4eMoVaREv8kAvo9A6TAsGS7meVrV8wG8i4e18b35Ew41rSd7_di0z2_2XYMP9RaxrVx5uZJmZ2VJ-CQl2EGM-Ietn97h1Ua-_HgE79em4yPSmqd0eVjqLtelGlISZCmSGB7qkNOcbdpekFyZ9Ci59ug1BNnKb6E42mYSmFkiTDDL7XnRm1wgKSHKWkSWkgkGSFRu2DO3VgrI11N7d8mdG9pgdt983gWwc0MMezqOsWY80VLoEw_3FTQhP8cozUigJ2YvHEFDwtS9JGeolh-fdX3VhS7ttT1-tGA-y4YLicfkQxAqI618OInIewB2ypWhK1BjmmgHFS7lxS8nfTiLYlm4KHkTRCZTV0vgTh6IMGwkOVXMowJ-00yFDJBgTJl9CAsM7blgCEK73B0JESv_bp6PglKY7ZBh-gu01mnM3krEcw4tqSAH-Tl2ED_hf_j7dfNzU_suMKLoi0ayGb0IJlWiogQXWp2uobHLKEpHXdBnHX_1xvxanHkUrO0-1AogzCeYcRr9rE0W8a2cfIWHKR361RiIMo2AGB4tNzsUdh0mtCi_6Y94n7mUKCdHQOmcPRuJqcz14CEEDtCQLAWwMMhkwdjT7KwF4XGHatM5k_cXQoQiSyZVwdNPx6_5Xj7kJy0-B-NH6M7uI3OcVTJNVW3cc4iE="}}
|
||
{"timestamp":"2025-09-22T16:09:46.562Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"pwsh.exe\",\"-NoLogo\",\"-Command\",\"Get-Content -Path \\\"NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs\\\"\"],\"workdir\":\"C:\\\\GitCode\\\\paiban\"}","call_id":"call_fEFYweP4SsSDEIIyz90Cvzix"}}
|
||
{"timestamp":"2025-09-22T16:09:46.562Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_fEFYweP4SsSDEIIyz90Cvzix","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 /// 增强版线性规划引擎 - 实现遗传算法中的所有复杂约束\\n /// 核心功能：三级约束体系 + 多维度目标优化 + 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，实现精确求解\\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 // 求解器配置 - 增强版配置支持复杂约束\\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; // 增加到10分钟支持复杂约束\\n private const int MAX_CONSTRAINT_COUNT = 50000; // 最大约束数量限制\\n \\n // 约束权重配置 - 对应遗传算法的三级约束体系\\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; // 公平性奖励系数\\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化 - 实现遗传算法等价的约束体系\\n /// 业务流程：构建决策变量 → 三级约束建模 → 多目标优化 → 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化 - 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：创建高性能求解器\\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证 \\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：公平性约束 - 对应遗传算法的负载均衡机制\\n AddFairnessConstraints(solver, decisionVariables, auxiliaryVariables, context);\\n\\n // 第八步：设置多维度目标函数 - 对应遗传算法的适应度函数\\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型...\\\");\\n var re\\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常 - 任务{TaskId}人员{PersonnelId}，默认为不可用\\\", \\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展\\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 - 支持高效的关联查询\\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 }\\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 // 关联对象也需要复制\\n ShiftEntity = original.ShiftEntity,\\n ProcessEntity = original.ProcessEntity,\\n WorkOrderFLPersonnels = original.WorkOrderFLPersonnels\\n };\\n }\\n }\\n\\n /// <summary>\\n /// 解质量指标\\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\":1.0}}"}}
|
||
{"timestamp":"2025-09-22T16:09:46.563Z","type":"turn_context","payload":{"cwd":"C:\\GitCode\\paiban","approval_policy":"on-request","sandbox_policy":{"mode":"workspace-write","network_access":false,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
|
||
{"timestamp":"2025-09-22T16:09:49.468Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Preparing to locate CreateAdvancedSolver method**"}}
|
||
{"timestamp":"2025-09-22T16:09:53.949Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":17050,"cached_input_tokens":10112,"output_tokens":642,"reasoning_output_tokens":448,"total_tokens":17692},"last_token_usage":{"input_tokens":7577,"cached_input_tokens":4992,"output_tokens":143,"reasoning_output_tokens":64,"total_tokens":7720},"model_context_window":272000}}}
|
||
{"timestamp":"2025-09-22T16:09:53.949Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Preparing to locate CreateAdvancedSolver method**"}],"content":null,"encrypted_content":"gAAAAABo0XTORlmVe6GiEM1r37OmaCyWD9fwhlHDkyn7T-xyLG63m7VMrf9DYAQI8rhd67pNU1y6u7Rqy-KgU3dG8p6a76OKsjQm1ImsmmUaTaJk1Tx3_AyC5bFaXrPDGoX1Vi0g6zNMTIlJ7daxNB-IDK_oWnjkct1A-1kh4wkKYYzIUpaQ-rvRZcvxwf-z4NBQxjh3uPHV5qX0WLdgwrJZk5mVZXGJabNtmoTUfPPGk--sS3LPE9ZGFZbpzg4hC9skTb8aQJEvcYUTgWz2FLzqAbfzvvSaPcUR4qh_7o6SdRcOXJhctl7qsgzRyyKFzrqlh5v_P_J9_MH8WhTtZ3PS2xjR_35jLFei4vAgrOATWHe21xWm3FlZekzKweCRHK2VXmzVXLBLKzJr0L7VAoEObbbIvFdKcvFZ7BUHG6e7JaFger-3n7p28uzbFz50EBVW-YWdAtMRA5O783MPjKmylgij42kxxf41Q0K8HNYU478JUPNR4y15CMvWMxl5h6hWhiQMuNuiBTkS6R5Y0u9bincltAztZPutVHRM4B6nOH6L35GgEDz3S7IPqOeT4qS8yKxjtr9BheDVo0Yo-ypIvKnhnKMJLrHsAYcFI-sTQIK7FaIx1L_KKZXz9u5ewYcj5SZCrSWsrys8y0DBovaLauF6Z2lZwZHLyogG0LHcuGIgDBP3bUQH-6MA_IURjq8gfLeGIFUd-mHkz5rrmGRGn9j4KSfpPxqdjj13IPvBVbbOR_6z9gZTtJz3GkCEyta7zvxK1lzBzvzo5RIy-9AkUSecmd4gyLkY8QTubYvLGhIDbfK_gv8wnhfja1c4ONm2Z8X-C20st0OFocYkutVOWH082QnF7teueichVt2YcZuOOJ5GxRpwCa4mVBRKL-JTQl-PHfqqLqZXtIt90lxG8aKPSAl9vB4RSKeV6VzpuS0t8s0FZ45xp4N5qn8NbjrQDqWHL89Tan3f82jl0oEj05np_FX-haqs9YC4fBQIcnbHRUdUQCQ7-cbUxqtiLqwebe3_9I-O5-A6TDrHFU8DdG376ThHd2iRbViJD8oxubKb6Ip8d0blYFVXUp0WkAEzvQA56BxztXo5RpWyjZuVKy_qPgVfnoluUpkJLr9j99YWTocmGVTsTDz19bHk31RdDHpo7E42XbAScsiF6BuPnDLtePqKUS5AhmF2end1xMfMmpk1du-Qtvy95ZJejhu73ByuJi15nBv_luSMLBQAfelwHDeTFdj6MmYCSHuIkLtL-mIecG48gJm1zLvKWcDhqj_ObRwszS3MO7Fbnmt3_Lfyk2dak_AJUxyLYBNlfPPyR4Om1FGYeHjmirmuNpwaKx1Bwo8KgfNQF1s2wlCeGPxAgOWjn0mfQuh61VCF1HjzkQzXxWnXoSFg_iMBi9ALKT-F644z79rTvfHJlVc9Ik6djgti-g=="}}
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{"timestamp":"2025-09-22T16:09:53.949Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"pwsh.exe\",\"-NoLogo\",\"-Command\",\"Select-String -Path \\\"NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs\\\" -Pattern \\\"CreateAdvancedSolver\\\" -Context 0,80\"],\"workdir\":\"C:\\\\GitCode\\\\paiban\"}","call_id":"call_pRWTdO9GcMh3E0nk3Y6Ls6aw"}}
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{"timestamp":"2025-09-22T16:09:53.949Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_pRWTdO9GcMh3E0nk3Y6Ls6aw","output":"{\"output\":\"\\n> NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:61: using var solver = \\u001b[7mCreateAdvancedSolver\\u001b[0m();\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:62:\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:63: // 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)\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:64: var decisionVariables = BuildDecisionVariables(solver, context);\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:65: _logger.LogDebug(\\\"📊 决策变量构建完成 - 变量数量：{VariableCount}\\\",\\u001b[0m\\n\\u001b[7m\\u001b[0m decisionVariables.Count);\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:66:\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:67: // 第三步：构建辅助变量 (支持复杂约束建模)\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:68: var auxiliaryVariables = BuildAuxiliaryVariables(solver, context, d\\u001b[0m\\n\\u001b[7m\\u001b[0mecisionVariables);\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:69: _logger.LogDebug(\\\"🔧 辅助变量构建完成 - 辅助变量数量：{AuxCount}\\\", \\u001b[0m\\n\\u001b[7m\\u001b[0mauxiliaryVariables.Count);\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:70:\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:71: // 第四步：Level 1 基础约束 - 对应遗传算法的基础约束验证\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:72: await AddLevel1BasicConstraints(solver, decisionVariables, auxiliar\\u001b[0m\\n\\u001b[7m\\u001b[0myVariables, context);\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:73:\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:74: // 第五步：Level 2 组合约束 - 对应遗传算法的组合约束验证 \\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:75: await AddLevel2CombinationConstraints(solver, decisionVariables, au\\u001b[0m\\n\\u001b[7m\\u001b[0mxiliaryVariables, context);\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:76:\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:77: // 第六步：Level 3 业务约束 - 对应遗传算法的业务逻辑约束\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:78: await AddLevel3BusinessConstraints(solver, decisionVariables, auxil\\u001b[0m\\n\\u001b[7m\\u001b[0miaryVariables, context);\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:79:\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:80: // 第七步：公平性约束 - 对应遗传算法的负载均衡机制\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:81: AddFairnessConstraints(solver, decisionVariables, auxiliaryVariable\\u001b[0m\\n\\u001b[7m\\u001b[0ms, context);\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:82:\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:83: // 第八步：设置多维度目标函数 - 对应遗传算法的适应度函数\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:84: SetEnhancedObjectiveFunction(solver, decisionVariables, auxiliaryVa\\u001b[0m\\n\\u001b[7m\\u001b[0mriables, context);\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:85:\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:86: // 第九步：执行求解\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:87: _logger.LogInformation(\\\"🔍 开始求解增强版线性规划模型...\\\");\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:88: var resultStatus = solver.Solve();\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:89: \\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:90: stopwatch.Stop();\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:91: \\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngi\\n[... omitted 0 of 155 lines ...]\\n\\n\\u001b[7m\\u001b[0m保守评估）\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:169: if (prefilterResult.IsFeasible || prefilterResult.Prefilte\\u001b[0m\\n\\u001b[7m\\u001b[0mrScore > 30.0)\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:170: {\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:171: var variableName = $\\\"x_{task.Id}_{personnel.Id}\\\";\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:172: var variable = solver.MakeBoolVar(variableName);\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:173: variables[(task.Id, personnel.Id)] = variable;\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:174: createdCount++;\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:175: }\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:176: else\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:177: {\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:178: skippedCount++;\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:179: }\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:180: }\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:181: else\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:182: {\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:183: // 【Ultra think优化3】无预筛选数据时的保守策略\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:184: // 即使无预筛选数据，但已通过不可用性检查，仍创建变量\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:185: var variableName = $\\\"x_{task.Id}_{personnel.Id}\\\";\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:186: var variable = solver.MakeBoolVar(variableName);\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:187: variables[(task.Id, personnel.Id)] = variable;\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:188: createdCount++;\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:189: }\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:190: }\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:191: }\\u001b[0m\\n\\u001b[7m\\u001b[0m NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs:192:\\u001b[0m\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.9}}"}}
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{"timestamp":"2025-09-22T16:09:53.949Z","type":"turn_context","payload":{"cwd":"C:\\GitCode\\paiban","approval_policy":"on-request","sandbox_policy":{"mode":"workspace-write","network_access":false,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
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{"timestamp":"2025-09-22T16:09:59.252Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Investigating method extraction techniques**"}}
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{"timestamp":"2025-09-22T16:10:03.162Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":27925,"cached_input_tokens":17664,"output_tokens":841,"reasoning_output_tokens":576,"total_tokens":28766},"last_token_usage":{"input_tokens":10875,"cached_input_tokens":7552,"output_tokens":199,"reasoning_output_tokens":128,"total_tokens":11074},"model_context_window":272000}}}
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{"timestamp":"2025-09-22T16:10:03.162Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Investigating method extraction techniques**"}],"content":null,"encrypted_content":"gAAAAABo0XTX2PuKH1IW4TtIiZDdQsK2ZAS-_tIQoQeZJo2993WoiI2e2DeTqzmMjL7IL6VdU3mmB3Yn_yPsx_jGxE14046dDMIXMhRQFjvhf8dl25kWnDBrbsbiU2TxjNPBZ4gnkDmWUDb2RexQu1BC4jGGRzs9_jUBMt-nXmjCRx5xVWh0EAdBbd2OJEaNmasFmBgxS1DpVLtmGJKleVANI26TDKfnCFBrVtmGUDeFmRyFb0a-zuJXnpxI3sca1U8iiQ0SuidX7GxQrFwZqr877ENzmVtc1-1eouAVEP-BPywhjq3he2hRoTOR50PmmQWtJYcZjiIcH0qwYFh8iYCg-YWQY5J9FlGREPTK2dLOt4QS90pgYdWEOvdp--H0A94L5WNjco5Vm1Byihohr6WFRDri2mDjtCZOWINh5dkV_mPp_yj-x2-ZBFLXsiCiC05vFagw634h7Pftz33QGnWeLB0J9_wAtfSFMs-ikjhaN8ZHAYksbTrKbFOM3X9wTF5Yde7qF4IFQK245mOcTnzGuiOzRmvNqQCBMv7dVq3M-qCjj3-Qba9KCfhO_2q40GiTIRTvwmoPTtEjj25_jpHQZSNzAGZzXXD6rURjmbwk4SOAgCSLTrFh02XHZlBSvmbaVhC0l0RMBuMDH_6sttozjh0gmEXtiI8TaB2inl6t5p6osmNaA9abrH6zMXXbrg3N8bM2IoEg676QFA1rY8RX0yPxClma7U5foe9ejgx4pi5m3kuMjp8LUmetNc50ia8_HSM1FiSLW7mYgFYrDasLOV_V9My1ghD058rFK5krc2j70o8rdNDIWoYFvXsciP8LpHHg_RsF2ONwfqqeMSrqcgMt1OSVssT2ibWKljNfJcz6EuXDn5YNsimYUS_nucF3nkRIvX2q9hTKrjQzmKtyN9q6EFTHvUXpUMzF4xtKsCB7PWYJ3NKfKgFH38UoKkCSxChgkQskiw4ryPis5fQKijEv79iHPl2UkizLcqjlqrzDj78zuf6amaGs7Mi20IPn3Dfa82rtSmVN9kqG8Hvqr1KoxH0UUiXjq4eIAzqrfZGsDG3CcNgH1M4MApnJl3Puo1UUA0CMAzJZ4L51_GmStWGBl2AmRkm9nKhEOU4E2--Dhy4N09IE1sZyhnZXA0DtF3yI95W-CBrurZoFxIImtgf3DAyBT_K_wm9CEW1UGiZbiJqiEO6cj3iT0b-hjZejhSy89K_JjiolUqYMslJHa_dQj1R-MpjFDcK2Xp_ne0a6YPFrpd4XaO-S7oHszjkL9beQn5Ym9JiciPAo6VhsdKGQHQaHjWcY_dhB-EZYDsC7dzXOxKH7ail1Ape_R-9oo7ZXOyhIsrGrmexsJDlImHRZV_l9YJ4xmSEO2Fpy60RD1vkiZ7A_JOD8X4ZM8mI6_joxJYcrIqVKxW43ii3KobbSUVa-UASydtxfnajAb3lgcIe3VHYIeZTxN1daMTVfsjCQjBr84Z1ry_EzxNmBUk8STskGIa1CAars-BCi7NCfy9oMfT9XZr8clkBoINdOFafBRr43rIwNIgfROZc7Mzl9Dl85fmClXyOAkAxvYsFnFi7aFAuYN_aW3PuLMTvhWZx1INBGW2bkunOBahgc_jvFndCnWNUcj21QEMvaDHaV8nELUDbIrg6Oq8qtpx2tVbWpBq6Ij4gp2AnagAg_s71QU6PC0wevM--q7ttZbiUHPp0pfMs="}}
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{"timestamp":"2025-09-22T16:10:03.162Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"pwsh.exe\",\"-NoLogo\",\"-Command\",\"Get-Content -Path \\\"NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs\\\" -TotalCount 200\"],\"workdir\":\"C:\\\\GitCode\\\\paiban\"}","call_id":"call_Wb7EHpk9HDZymT2sI6K62DpP"}}
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{"timestamp":"2025-09-22T16:10:03.162Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_Wb7EHpk9HDZymT2sI6K62DpP","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 /// 增强版线性规划引擎 - 实现遗传算法中的所有复杂约束\\n /// 核心功能：三级约束体系 + 多维度目标优化 + 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，实现精确求解\\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 // 求解器配置 - 增强版配置支持复杂约束\\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; // 增加到10分钟支持复杂约束\\n private const int MAX_CONSTRAINT_COUNT = 50000; // 最大约束数量限制\\n \\n // 约束权重配置 - 对应遗传算法的三级约束体系\\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; // 公平性奖励系数\\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化 - 实现遗传算法等价的约束体系\\n /// 业务流程：构建决策变量 → 三级约束建模 → 多目标优化 → 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化 - 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：创建高性能求解器\\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证 \\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：公平性约束 - 对应遗传算法的负载均衡机制\\n AddFairnessConstraints(solver, decisionVariables, auxiliaryVariables, context);\\n\\n // 第八步：设置多维度目标函数 - 对应遗传算法的适应度函数\\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型...\\\");\\n var re\\n[... omitted 0 of 200 lines ...]\\n\\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\\n /// <summary>\\n /// 【Ultra think增强】构建决策变量 - 集成人员班次不可用性的智能变量生成\\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\\n /// 【三层优化】：预筛选结果 + 不可用性检查 + 评分阈值，实现精确的变量裁剪\\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\\n /// </summary>\\n private Dictionary<(long TaskId, long PersonnelId), Variable> BuildDecisionVariables(\\n Solver solver, GlobalAllocationContext context)\\n {\\n var variables = new Dictionary<(long TaskId, long PersonnelId), Variable>();\\n var createdCount = 0;\\n var skippedCount = 0;\\n var unavailabilitySkippedCount = 0;\\n \\n foreach (var task in context.Tasks)\\n {\\n foreach (var personnel in context.AvailablePersonnel)\\n {\\n var prefilterKey = $\\\"{task.Id}_{personnel.Id}\\\";\\n \\n // 【Ultra think优化1】首先检查人员班次不可用性 - 硬排除\\n if (IsPersonnelUnavailableForTask(task, personnel.Id, context))\\n {\\n unavailabilitySkippedCount++;\\n skippedCount++;\\n _logger.LogDebug(\\\"🚫 跳过不可用组合 - 任务{TaskId}人员{PersonnelId}在{Date}班次{ShiftId}不可用\\\", \\n task.Id, personnel.Id, task.WorkOrderDate.ToString(\\\"yyyy-MM-dd\\\"), task.ShiftId);\\n continue;\\n }\\n \\n // 【Ultra think优化2】基于预筛选结果的智能决策\\n if (context.PrefilterResults.TryGetValue(prefilterKey, out var prefilterResult))\\n {\\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）\\n if (prefilterResult.IsFeasible || prefilterResult.PrefilterScore > 30.0)\\n {\\n var variableName = $\\\"x_{task.Id}_{personnel.Id}\\\";\\n var variable = solver.MakeBoolVar(variableName);\\n variables[(task.Id, personnel.Id)] = variable;\\n createdCount++;\\n }\\n else\\n {\\n skippedCount++;\\n }\\n }\\n else\\n {\\n // 【Ultra think优化3】无预筛选数据时的保守策略\\n // 即使无预筛选数据，但已通过不可用性检查，仍创建变量\\n var variableName = $\\\"x_{task.Id}_{personnel.Id}\\\";\\n var variable = solver.MakeBoolVar(variableName);\\n variables[(task.Id, personnel.Id)] = variable;\\n createdCount++;\\n }\\n }\\n }\\n\\n _logger.LogDebug(\\\"📊 【增强版】决策变量构建统计 - 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}\\\", \\n createdCount, skippedCount, unavailabilitySkippedCount, \\n (double)createdCount / (createdCount + skippedCount),\\n (double)unavailabilitySkippedCount / (createdCount + skippedCount));\\n\\n return variables;\\n }\\n\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.9}}"}}
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{"timestamp":"2025-09-22T16:10:03.162Z","type":"turn_context","payload":{"cwd":"C:\\GitCode\\paiban","approval_policy":"on-request","sandbox_policy":{"mode":"workspace-write","network_access":false,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
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{"timestamp":"2025-09-22T16:10:08.252Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Inspecting method definition lines**"}}
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{"timestamp":"2025-09-22T16:10:12.671Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":41156,"cached_input_tokens":28672,"output_tokens":1113,"reasoning_output_tokens":768,"total_tokens":42269},"last_token_usage":{"input_tokens":13231,"cached_input_tokens":11008,"output_tokens":272,"reasoning_output_tokens":192,"total_tokens":13503},"model_context_window":272000}}}
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{"timestamp":"2025-09-22T16:10:12.671Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Inspecting method definition lines**"}],"content":null,"encrypted_content":"gAAAAABo0XTgAs-FPgl2ezFF7E-IW2RtuamTNpKhxnPCIPZo4Ab7Ar_MzaTGXIXwpbwIUjyxJ1KxF4v8msZLkDbefr3J1WJTEIMFEY2JPSOud0xayp8NSIZewz6GBEDTWeEi8POdbgDsA0FO0z5qfmODNJ-Cjkavt86nsZNwVB8OgAO-7VVhP-JPnuiiuvPypHn2xUUJaYgrWgFbtGsS68hOxIuv7lDktQdgmHk1rqPAOuxLEDIi91_f-740De33ua7kORK3clnd06TcgQdF7D9e6gksN3N-LV-O35KycJxND97PpVKm56ibQWkiiIuBmg-YV3GveS1PQvG9pqMgl4QgCY6XEU5HSoa01_38uea9rLEDxR_OPLIS-radKT5Cg_e5gegVXhz39wzCFoSTDm8qNR4mHzJPirr7ZaTELkU5yFFaK3QOTNllcvoTJTQLO7jFzoLLR5hWRhU4jbRzOSMZ4eLRSOr5eE5ZS75K9QdlE9mlPYufhMoPWmXuL6eUDTZ9gvv1o6caDLgXR13xSSv69gQ5B_jBf4TXMPT0dpEgorMCQv7NUKfiplUOlkHu0Y6izE2OyGyvEMFHGu3rmgbV7zUSO1rXfk5lanWlf_0u6Gr9nOVd1VID_-kksJgGVR3C_gelKwU08u_QK9wKK17q-aJ8z-klc4R7tZVlddnj1MEyENnZ8_v1XXj-7b-UZyIb3-sMi8jLRptg2rFcEXB5GVHntPo_ezpSjUMF8hC0Fvzf5wWPPnTBFf62rXDcCTEqQqjrYeu3GDzZrEu9k3GwI5AE5QIFhiHlJvkff3WaU5f_6SrPfB1RTBmbzWoSJWwD8Q68_wYDTubUKQSIUifc1N8STTPB2Np0JIRAdcOxW2F68gS1Tbqz9uqZ2j89_8-MJR0Cj2IXdwlI4bz5wRXNzINWvLTy4pJcCBlWKudXUi0AC_RJcTD-hYgCoLUiTHRbzs96SfVjhX7J38aIPOmjun6wPwQ_cB4twRCSKpkR_semS1a6ihEhtWjKGdEuiSiCTWan1Hn3-bd_reFKQBbidbC5XcoFSNVz_UApqbRGJBuiizuxOrClundDdA-yQygRlhUWlI9B4Vq0z5mFhT0u4c4p7yGWZnH3W6WF9ROwD76MFktkwDiiJQYfUc2VPoVRxQ2mM14wmc1w_Kjc2IcU1699dLjIud2YATffO8a7gDHzBJUae62eaDSsaNFkTiOWBS9kBN4jkbUh7tYgdYCGzIR94q1YlMWhKuU6dbs6MJIB3eYnMhwRu_NIdTFgG8691jXktukJ_8aCIkAJH_r3HTOWpYnbMYb4BTaPwOAMDvcirrnwMebn694PniDrQMMkTJeBqhw5WpOorqZ2yB70jmW5D6R22CY2AptLtVEL13XeZIdZswX35GSEHnNiFrQQrp-eVkGnlKeWulyCrd-2dwKTp9XZOweWoQ8oP-Lm-PGYawN8pxypNS2G60-BspXp1JtwjweCtAbisvrGbElyVwfjS2-TlkbZ3k_xOdi0NMiwhTQkeY_URUzuHu6hMkbr65MbkJ39yAFehXymvrgkzmtvlGfCJWiqx6Q_CO72fY8qnJQByXNPsFpSvdlV_6nApy_yWtYSXuxwF20ClMSvawhXSqNqPqtopAaHju3PCg9x1zIqHh8GzpFcHSrNhO8nh2Cj_mBk3kfdoWPkT51bpkDBsRSU1HdG493gDwTjgX1GzuboYonkoz3ns9XdNYc3ACJNX66q02lSVxetVXtgdJYxH5n_GjAOQYLxaSvXrW_GyC5I1vdWKAMlDKCTgWToHvwv6fhOiX9pNrWrxMmvEfPPmCi88dISknmcWmBjXM3Q4fEQNZDEpVPd51ORXc9yPFmgv_7btRX8DJkR4tFR_QoMoyhfytxQhjccWiUh1G-4pWpdhCg="}}
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{"timestamp":"2025-09-22T16:10:12.671Z","type":"response_item","payload":{"type":"function_call","name":"shell","arguments":"{\"command\":[\"pwsh.exe\",\"-NoLogo\",\"-Command\",\"(Get-Content -Path \\\"NPP.SmartSchedue.Api\\\\Services\\\\Integration\\\\Algorithms\\\\LinearProgrammingEngine.cs\\\" | Select-Object -Skip 100 -First 80)\"],\"workdir\":\"C:\\\\GitCode\\\\paiban\"}","call_id":"call_L275eCaDOzMLuJ5G9BnlheQv"}}
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{"timestamp":"2025-09-22T16:10:12.671Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_L275eCaDOzMLuJ5G9BnlheQv","output":"{\"output\":\" _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 /// 创建高性能求解器 - 支持大规模约束优化\\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\\r\\n /// <summary>\\r\\n /// 【Ultra think增强】构建决策变量 - 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】：预筛选结果 + 不可用性检查 + 评分阈值，实现精确的变量裁剪\\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性 - 硬排除\\r\\n if (IsPersonnelUnavailableForTask(task, personnel.Id, context))\\r\\n {\\r\\n unavailabilitySkippedCount++;\\r\\n skippedCount++;\\r\\n _logger.LogDebug(\\\"🚫 跳过不可用组合 - 任务{TaskId}人员{PersonnelId}在{Date}班次{ShiftId}不可用\\\", \\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\":1.0}}"}}
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{"timestamp":"2025-09-22T16:10:12.672Z","type":"turn_context","payload":{"cwd":"C:\\GitCode\\paiban","approval_policy":"on-request","sandbox_policy":{"mode":"workspace-write","network_access":false,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5-codex","effort":"high","summary":"auto"}}
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{"timestamp":"2025-09-22T16:10:14.243Z","type":"event_msg","payload":{"type":"turn_aborted","reason":"interrupted"}}
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