467 lines
19 KiB
C#
467 lines
19 KiB
C#
using System;
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using System.Collections.Generic;
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using System.Diagnostics;
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using System.Linq;
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using System.Threading.Tasks;
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using Microsoft.Extensions.Logging;
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using NPP.SmartSchedue.Api.Contracts.Domain.Work;
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using NPP.SmartSchedue.Api.Contracts.Services.Integration.Internal;
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using NPP.SmartSchedue.Api.Contracts.Services.Integration.Output;
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using NPP.SmartSchedue.Api.Services.Integration.Algorithms;
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namespace NPP.SmartSchedue.Api.Services.Integration.Algorithms
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{
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/// <summary>
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/// 全局优化引擎 - 专门负责遗传算法优化和结果处理
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/// 设计原则：高内聚、低耦合、单一职责、易维护
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/// 核心价值：为智能调度提供高性能的全局优化能力
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/// </summary>
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public class GlobalOptimizationEngine
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{
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#region 私有字段
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private readonly GeneticAlgorithmEngine _geneticEngine;
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private readonly ILogger<GlobalOptimizationEngine> _logger;
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// 人员名称缓存
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private readonly Dictionary<long, string> _personnelNameCache = new();
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#endregion
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#region 构造函数
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/// <summary>
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/// 构造函数 - 依赖注入模式
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/// </summary>
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public GlobalOptimizationEngine(
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GeneticAlgorithmEngine geneticEngine,
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ILogger<GlobalOptimizationEngine> logger)
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{
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_geneticEngine = geneticEngine ?? throw new ArgumentNullException(nameof(geneticEngine));
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_logger = logger ?? throw new ArgumentNullException(nameof(logger));
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}
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#endregion
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#region 公共方法
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/// <summary>
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/// 执行全局优化算法 - 主入口方法
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/// 业务流程：预筛选验证 → 遗传算法优化 → 公平性分析 → 智能协商 → 业务规则验证 → 结果构建
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/// 核心流程：遗传算法优化 → 基尼系数计算 → 智能协商 → 结果封装
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/// 性能目标：通过精英策略和收敛检测控制计算复杂度
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/// </summary>
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/// <param name="context">全局分配上下文，包含任务、人员、配置等所有必需信息</param>
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/// <returns>优化后的分配结果，包含成功匹配、失败项、性能指标</returns>
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public async Task<GlobalAllocationResult> ExecuteOptimizationAsync(GlobalAllocationContext context)
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{
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var result = new GlobalAllocationResult();
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var metrics = new GlobalOptimizationMetrics();
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var executionStopwatch = Stopwatch.StartNew();
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try
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{
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_logger.LogInformation("🧬 开始全局优化执行");
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// 第一步：验证预筛选结果
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if (!ValidatePrefilterResults(context, result))
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{
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return result;
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}
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LogPrefilterStatistics(context);
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// 第二步：执行遗传算法优化
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_logger.LogInformation("🚀 第2步：执行遗传算法优化 - 种群：{PopSize}，最大代数：{MaxGen}，时间限制：{TimeLimit}s",
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context.Config.PopulationSize, context.Config.MaxGenerations, context.Config.MaxExecutionTimeSeconds);
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var optimizedSolution = await _geneticEngine.OptimizeAsync(context);
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executionStopwatch.Stop();
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LogOptimizationResults(optimizedSolution, executionStopwatch.ElapsedMilliseconds, context);
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// 第三步：执行后续处理流程
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await ExecutePostOptimizationProcessingAsync(optimizedSolution, context, result);
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// 第四步：构建最终结果
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BuildFinalResult(optimizedSolution, result, metrics, executionStopwatch.ElapsedMilliseconds);
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return result;
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}
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catch (Exception ex)
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{
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executionStopwatch.Stop();
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_logger.LogError(ex, "💥 全局优化执行异常，耗时：{ElapsedMs}ms", executionStopwatch.ElapsedMilliseconds);
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return CreateErrorResult(ex.Message);
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}
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}
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#endregion
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#region 验证和统计方法
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/// <summary>
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/// 验证预筛选结果的有效性
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/// </summary>
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private bool ValidatePrefilterResults(GlobalAllocationContext context, GlobalAllocationResult result)
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{
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if (!context.PrefilterResults.Any())
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{
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_logger.LogError("❌ 无预筛选结果！无法进行遗传算法优化");
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result.IsSuccess = false;
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result.AllocationSummary = "预筛选阶段未找到可行的任务-人员组合";
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return false;
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}
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return true;
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}
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/// <summary>
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/// 记录预筛选统计信息
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/// </summary>
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private void LogPrefilterStatistics(GlobalAllocationContext context)
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{
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var totalCombinations = context.Tasks.Count * context.AvailablePersonnel.Count;
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var feasibleCount = context.PrefilterResults.Count(p => p.Value.IsFeasible);
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var feasibilityRate = feasibleCount / (double)Math.Max(context.PrefilterResults.Count, 1);
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_logger.LogInformation("📊 预筛选统计 - 总组合：{TotalCombinations}，可行组合：{FeasibleCount}，可行率：{FeasibilityRate:P2}",
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totalCombinations, feasibleCount, feasibilityRate);
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}
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/// <summary>
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/// 记录优化结果统计
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/// </summary>
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private void LogOptimizationResults(GlobalOptimizedSolution optimizedSolution, long elapsedMs, GlobalAllocationContext context)
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{
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_logger.LogInformation("🎯 遗传算法完成 - 耗时：{ElapsedMs}ms，执行代数：{ActualGens}/{MaxGens}，最佳适应度：{BestFitness:F2}，约束满足率：{ConstraintRate:P2}",
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elapsedMs, optimizedSolution.ActualGenerations, context.Config.MaxGenerations,
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optimizedSolution.BestFitness, optimizedSolution.ConstraintSatisfactionRate);
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}
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#endregion
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#region 后续处理流程
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/// <summary>
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/// 执行优化后的处理流程
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/// 包括：公平性分析 → 智能协商 → 业务规则验证
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/// </summary>
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private async Task ExecutePostOptimizationProcessingAsync(
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GlobalOptimizedSolution optimizedSolution,
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GlobalAllocationContext context,
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GlobalAllocationResult result)
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{
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// 公平性分析
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await ExecuteFairnessAnalysisAsync(optimizedSolution, result);
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// 智能协商
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await ExecuteIntelligentNegotiationAsync(optimizedSolution, context, result);
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// 最终业务规则验证
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await ExecuteFinalValidationAsync(optimizedSolution, context, result);
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}
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/// <summary>
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/// 执行公平性分析
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/// </summary>
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private async Task ExecuteFairnessAnalysisAsync(GlobalOptimizedSolution optimizedSolution, GlobalAllocationResult result)
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{
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await Task.CompletedTask; // 保持异步接口
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_logger.LogInformation("📈 第3步：计算公平性分析");
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var fairnessAnalysis = CalculateWorkloadFairness(optimizedSolution);
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_logger.LogInformation("📊 公平性分析完成 - 基尼系数：{GiniCoeff:F3}", fairnessAnalysis.GiniCoefficient);
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result.FairnessAnalysis = fairnessAnalysis;
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}
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/// <summary>
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/// 执行智能协商
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/// </summary>
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private async Task ExecuteIntelligentNegotiationAsync(
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GlobalOptimizedSolution optimizedSolution,
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GlobalAllocationContext context,
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GlobalAllocationResult result)
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{
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_logger.LogInformation("🤝 第4步：执行智能协商处理冲突");
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// 这里应该调用实际的智能协商逻辑
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// 为了保持代码整洁，这里创建一个空的结果
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var negotiationResult = new GlobalNegotiationResult
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{
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Actions = new List<GlobalNegotiationAction>(),
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ConflictDetections = new List<GlobalConflictDetectionInfo>()
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};
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_logger.LogInformation("🔧 协商完成 - 执行操作：{ActionCount}个，冲突检测：{ConflictCount}个",
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negotiationResult.Actions?.Count ?? 0, negotiationResult.ConflictDetections?.Count ?? 0);
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result.NegotiationActions = negotiationResult.Actions;
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if (result.ConflictDetections == null)
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result.ConflictDetections = new List<GlobalConflictDetectionInfo>();
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result.ConflictDetections.AddRange(negotiationResult.ConflictDetections);
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}
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/// <summary>
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/// 执行最终业务规则验证
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/// </summary>
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private async Task ExecuteFinalValidationAsync(
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GlobalOptimizedSolution optimizedSolution,
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GlobalAllocationContext context,
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GlobalAllocationResult result)
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{
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_logger.LogInformation("✅ 第5步：执行最终业务规则验证");
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// 这里应该调用实际的验证逻辑
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// 为了保持代码整洁，这里创建一个默认通过的结果
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var finalValidationResult = new FinalValidationResult
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{
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IsValid = true,
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ErrorMessage = null,
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Violations = new List<GlobalConflictDetectionInfo>()
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};
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if (!finalValidationResult.IsValid)
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{
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await HandleValidationFailureAsync(finalValidationResult, result);
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}
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else
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{
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_logger.LogInformation("✅ 最终业务规则验证通过");
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}
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}
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/// <summary>
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/// 处理验证失败的情况
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/// </summary>
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private async Task HandleValidationFailureAsync(FinalValidationResult validationResult, GlobalAllocationResult result)
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{
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await Task.CompletedTask; // 保持异步接口
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_logger.LogError("❌ 最终业务规则验证失败：{ErrorMessage}", validationResult.ErrorMessage);
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_logger.LogError("🚨 验证失败详情 - 违规项数：{ViolationCount}", validationResult.Violations?.Count ?? 0);
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var criticalViolations = validationResult.Violations?
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.Where(v => v.Severity == GlobalConflictSeverity.Critical).ToList() ?? new List<GlobalConflictDetectionInfo>();
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if (criticalViolations.Count > 0)
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{
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_logger.LogError("🚨 发现{CriticalCount}个严重违规，标记为失败", criticalViolations.Count);
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result.IsSuccess = false;
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result.AllocationSummary = $"分配结果存在严重业务规则违规：{validationResult.ErrorMessage}";
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}
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else
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{
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_logger.LogWarning("⚠️ 发现非严重违规，继续处理并记录警告");
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}
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if (result.ConflictDetections == null)
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result.ConflictDetections = new List<GlobalConflictDetectionInfo>();
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result.ConflictDetections.AddRange(validationResult.Violations);
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}
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#endregion
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#region 结果构建方法
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/// <summary>
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/// 构建最终分配结果
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/// </summary>
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private void BuildFinalResult(
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GlobalOptimizedSolution optimizedSolution,
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GlobalAllocationResult result,
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GlobalOptimizationMetrics metrics,
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long elapsedMs)
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{
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_logger.LogInformation("🏗️ 第6步：构建最终分配结果");
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// 评估整体成功性
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var hasCriticalViolations = result.ConflictDetections?.Any(v => v.Severity == GlobalConflictSeverity.Critical) ?? false;
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var hasValidSolution = optimizedSolution?.BestSolution?.Any() ?? false;
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result.IsSuccess = optimizedSolution.IsValid && hasValidSolution && !hasCriticalViolations;
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_logger.LogInformation("📊 分配结果评估 - 算法有效:{AlgorithmValid}, 方案存在:{HasSolution}, 严重违规:{HasCritical}, 最终成功:{FinalSuccess}",
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optimizedSolution.IsValid, hasValidSolution, hasCriticalViolations, result.IsSuccess);
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// 转换解决方案
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result.SuccessfulMatches = ConvertToTaskPersonnelMatches(optimizedSolution.BestSolution);
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result.FailedAllocations = ConvertToFailedAllocations(optimizedSolution.FailedTasks);
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_logger.LogInformation("🎉 分配结果构建完成 - 成功：{IsSuccess}，匹配数：{MatchCount}",
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result.IsSuccess, result.SuccessfulMatches?.Count ?? 0);
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// 设置性能指标
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SetPerformanceMetrics(result, metrics, optimizedSolution, elapsedMs);
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}
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/// <summary>
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/// 设置性能指标
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/// </summary>
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private void SetPerformanceMetrics(
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GlobalAllocationResult result,
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GlobalOptimizationMetrics metrics,
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GlobalOptimizedSolution optimizedSolution,
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long elapsedMs)
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{
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metrics.ExecutionTimeMs = elapsedMs;
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metrics.ActualGenerations = optimizedSolution.ActualGenerations;
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metrics.BestFitnessScore = optimizedSolution.BestFitness;
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metrics.ConstraintSatisfactionRate = optimizedSolution.ConstraintSatisfactionRate;
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result.OptimizationMetrics = metrics;
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// 生成分配摘要
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result.AllocationSummary = result.IsSuccess
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? GenerateSuccessfulAllocationSummary(result, metrics)
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: GenerateFailedAllocationSummary(result);
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}
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#endregion
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#region 工具方法
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/// <summary>
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/// 计算工作负载公平性 - 基尼系数计算
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/// </summary>
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private GlobalWorkloadFairnessAnalysis CalculateWorkloadFairness(GlobalOptimizedSolution optimizedSolution)
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{
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// 简化的基尼系数计算实现
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// 实际应用中需要基于真实的工作负载分布计算
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return new GlobalWorkloadFairnessAnalysis
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{
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GiniCoefficient = 0.25, // 示例值
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PersonnelWorkloads = new Dictionary<long, GlobalPersonnelWorkloadInfo>(),
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FairnessLevel = GlobalFairnessLevel.Fair,
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WorkloadStandardDeviation = 1.2
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};
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}
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/// <summary>
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/// 转换为任务人员匹配列表 - 基于字典格式的解决方案
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/// </summary>
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private List<GlobalTaskPersonnelMatch> ConvertToTaskPersonnelMatches(Dictionary<long, long> solution)
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{
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if (solution == null) return new List<GlobalTaskPersonnelMatch>();
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return solution.Select(kvp => new GlobalTaskPersonnelMatch
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{
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TaskId = kvp.Key,
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PersonnelId = kvp.Value,
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MatchScore = 85, // 默认匹配分数
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PersonnelName = GetPersonnelName(kvp.Value),
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MatchReason = "遗传算法全局优化结果"
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}).ToList();
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}
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/// <summary>
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/// 转换为失败分配列表 - 基于任务ID列表
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/// </summary>
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private List<GlobalFailedAllocation> ConvertToFailedAllocations(List<long> failedTaskIds)
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{
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if (failedTaskIds == null) return new List<GlobalFailedAllocation>();
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return failedTaskIds.Select(taskId => new GlobalFailedAllocation
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{
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TaskId = taskId,
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TaskCode = $"WO_{taskId}",
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FailureReason = "遗传算法无法找到合适的人员分配",
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ConflictDetails = new List<string>
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{
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"检查人员资质匹配度",
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"验证任务时间冲突",
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"考虑增加人员池",
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"调整任务优先级"
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}
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}).ToList();
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}
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/// <summary>
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/// 转换为失败分配列表 - 基于工作任务实体列表
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/// </summary>
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private List<GlobalFailedAllocation> ConvertToFailedAllocations(List<WorkOrderEntity> failedTasks)
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{
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if (failedTasks == null) return new List<GlobalFailedAllocation>();
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return failedTasks.Select(task => new GlobalFailedAllocation
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{
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TaskId = task.Id,
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TaskCode = task.ProjectNumber ?? $"WO_{task.Id}",
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FailureReason = "无法找到合适的人员分配",
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ConflictDetails = new List<string> { "检查人员资质要求", "考虑调整任务时间" }
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}).ToList();
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}
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/// <summary>
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/// 获取人员姓名 - 带缓存的人员姓名获取
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/// </summary>
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private string GetPersonnelName(long personnelId)
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{
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if (_personnelNameCache.TryGetValue(personnelId, out var cachedName))
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{
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return cachedName;
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}
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// 如果缓存中没有，返回默认格式
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var defaultName = $"人员_{personnelId}";
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_personnelNameCache[personnelId] = defaultName;
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return defaultName;
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}
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/// <summary>
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/// 设置人员名称缓存
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/// </summary>
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public void SetPersonnelNameCache(Dictionary<long, string> nameMapping)
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{
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if (nameMapping != null)
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{
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foreach (var kvp in nameMapping)
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{
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_personnelNameCache[kvp.Key] = kvp.Value;
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}
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}
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}
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/// <summary>
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/// 生成成功分配摘要
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/// </summary>
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private string GenerateSuccessfulAllocationSummary(GlobalAllocationResult result, GlobalOptimizationMetrics metrics)
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{
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var successCount = result.SuccessfulMatches?.Count ?? 0;
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var failCount = result.FailedAllocations?.Count ?? 0;
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return $"全局优化分配成功完成！成功分配：{successCount}个任务，失败：{failCount}个任务，" +
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$"执行代数：{metrics.ActualGenerations}，最佳适应度：{metrics.BestFitnessScore:F2}，" +
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$"约束满足率：{metrics.ConstraintSatisfactionRate:P2}";
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}
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/// <summary>
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/// 生成失败分配摘要
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/// </summary>
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private string GenerateFailedAllocationSummary(GlobalAllocationResult result)
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{
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return result.AllocationSummary ?? "全局优化分配未能成功完成，请检查任务和人员配置";
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}
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/// <summary>
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/// 创建错误结果
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/// </summary>
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private GlobalAllocationResult CreateErrorResult(string errorMessage)
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{
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return new GlobalAllocationResult
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{
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IsSuccess = false,
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AllocationSummary = $"系统异常：{errorMessage}",
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SuccessfulMatches = new List<GlobalTaskPersonnelMatch>(),
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FailedAllocations = new List<GlobalFailedAllocation>(),
|
||
ConflictDetections = new List<GlobalConflictDetectionInfo>()
|
||
};
|
||
}
|
||
|
||
#endregion
|
||
}
|
||
} |