RCS-3000/src/dispatch/enhanced_agv_manager.h

#ifndef ENHANCED_AGV_MANAGER_H
#define ENHANCED_AGV_MANAGER_H

#include "agv_manager_base.h"
#include "resource_manager.h"
#include <unordered_map>
#include <functional>

/**
 * @brief AGV分配策略枚举
 */
enum class AssignmentStrategy {
    FIRST_FIT,          // 第一个适配（当前策略）
    NEAREST_FIT,        // 最近适配
    BATTERY_AWARE,      // 考虑电量
    LOAD_BALANCED,      // 负载均衡
    PRIORITY_BASED,      // 基于优先级
    COST_OPTIMAL         // 成本最优
};

/**
 * @brief AGV评估结果
 */
struct AGVEvaluation {
    AGV* agv;
    double score;              // 评估分数
    double estimated_time;     // 预计完成时间
    double distance_to_task;   // 到任务起点的距离
    std::string reason;        // 选择原因

    AGVEvaluation(AGV* a, double s, double t, double d, const std::string& r)
        : agv(a), score(s), estimated_time(t), distance_to_task(d), reason(r) {}
};

/**
 * @brief 任务分配选项
 */
struct AssignmentOption {
    Task* task;
    AGV* agv;
    std::vector<Path*> path;
    double total_cost;          // 总成本（时间、距离等）
    double estimated_duration;  // 预计执行时间
    double battery_consumption;  // 预计电量消耗

    AssignmentOption(Task* t, AGV* a, const std::vector<Path*>& p, double c, double d, double b)
        : task(t), agv(a), path(p), total_cost(c), estimated_duration(d), battery_consumption(b) {}
};

/**
 * @brief 增强的AGV管理器
 * 支持多种任务分配策略
 */
class EnhancedAGVManager : public AGVManagerBase {
private:
    AssignmentStrategy strategy_;  // 当前分配策略
    std::unordered_map<AssignmentStrategy, std::function<double(AGV*, Task*, double)>> scoring_functions_;
    ResourceManager* resource_manager_;  // 资源管理器集成

    // 分配权重
    struct AssignmentWeights {
        double distance_weight = 0.4;      // 距离权重
        double battery_weight = 0.3;       // 电量权重
        double load_weight = 0.2;          // 负载权重
        double speed_weight = 0.1;         // 速度权重
    } weights_;

public:
    EnhancedAGVManager(GraphMap* map, ResourceManager* resource_mgr = nullptr, AssignmentStrategy strategy = AssignmentStrategy::NEAREST_FIT)
        : AGVManagerBase(map), strategy_(strategy), resource_manager_(resource_mgr) {
        initializeScoringFunctions();
    }

    /**
     * @brief 设置资源管理器
     */
    void setResourceManager(ResourceManager* resource_mgr) {
        resource_manager_ = resource_mgr;
    }

    /**
     * @brief 设置分配策略
     */
    void setStrategy(AssignmentStrategy strategy) {
        strategy_ = strategy;
    }

    /**
     * @brief 设置分配权重
     */
    void setWeights(const AssignmentWeights& weights) {
        weights_ = weights;
    }

    /**
     * @brief 智能任务分配
     * 使用当前策略找到最优的AGV-任务匹配
     */
    int assignTasksSmart();

    /**
     * @brief 为特定任务寻找最佳AGV
     * @param task 要分配的任务
     * @param exclude_excluded 排除已分配任务的AGV
     * @return 评估结果列表，按分数排序
     */
    std::vector<AGVEvaluation> findBestAGVForTask(Task* task, bool exclude_assigned = true);

    /**
     * @brief 计算任务-AGV匹配的成本
     */
    double calculateAssignmentCost(AGV* agv, Task* task, std::vector<Path*>& path);

    /**
     * @brief 批量任务分配优化
     * 同时考虑多个任务，找到全局最优分配
     */
    std::vector<AssignmentOption> optimizeBatchAssignment(std::vector<Task*>& tasks,
                                                        std::vector<AGV*>& available_agvs);

    /**
     * @brief 预测AGV在未来时间段的可用性
     */
    std::pair<double, bool> predictAvailability(AGV* agv, double future_time);

    /**
     * @brief 获取AGV负载情况
     */
    double getAGVLoad(AGV* agv);

    /**
     * @brief 打印分配策略分析
     */
    void printAssignmentAnalysis();

    /**
     * @brief 完成任务并释放资源
     */
    void completeTaskWithResources(AGV* agv, bool success = true);

private:
    void initializeScoringFunctions();

    // 各种分配策略的评分函数
    double scoreFirstFit(AGV* agv, Task* task, double distance);
    double scoreNearestFit(AGV* agv, Task* task, double distance);
    double scoreBatteryAware(AGV* agv, Task* task, double distance);
    double scoreLoadBalanced(AGV* agv, Task* task, double distance);
    double scorePriorityBased(AGV* agv, Task* task, double distance);
    double scoreCostOptimal(AGV* agv, Task* task, double distance);

    // 辅助函数
    double calculateDistance(AGV* agv, Task* task);
    double calculateBatteryConsumption(AGV* agv, Task* task, double distance);
    double calculateLoadFactor(AGV* agv);
    std::vector<Path*> findPathWithAvoidance(AGV* agv, Task* task);
    std::string getReasonForSelection(AGV* agv, Task* task, double distance, double score);
    std::string agvStateToString(AGVState state);

    // 新增辅助方法
    bool assignSingleTask(AGV* agv, Task* task);
    std::string assignmentStrategyToString(AssignmentStrategy strategy);
};

/**
 * @brief 任务分配分析器
 * 用于分析和优化分配策略
 */
class AssignmentAnalyzer {
private:
    struct Metrics {
        double avg_completion_time;
        double agv_utilization;
        double battery_efficiency;
        int task_count;
        int reassignments;
    };

    std::unordered_map<AssignmentStrategy, Metrics> strategy_metrics_;

public:
    /**
     * @brief 记录任务分配结果
     */
    void recordAssignment(AssignmentStrategy strategy, AGV* agv, Task* task,
                         double completion_time, double battery_used);

    /**
     * @brief 获取最优策略
     */
    AssignmentStrategy getOptimalStrategy();

    /**
     * @brief 生成分配报告
     */
    void generateReport();

    /**
     * @brief 重置统计数据
     */
    void reset();
};

#endif // ENHANCED_AGV_MANAGER_H