Merge remote-tracking branch 'origin/tl'

src/main/java/com/aps/entity/Algorithm/Chromosome.java

@@ -32,6 +32,11 @@ public class Chromosome {
     /// </summary>
     private List<Integer> machineSelection;
 
+    // 缓存标记
+    private transient boolean machineStrDirty = true;
+    private transient boolean operationStrDirty = true;
+    private transient boolean geneStrDirty = true;
+
     /// <summary>
     /// 工序排序部分（工件/订单ID）
     /// </summary>
@@ -43,32 +48,53 @@ public class Chromosome {
     private String geneStr;
 
     public String  getGeneStr() {
-        geneStr=getMachineStr()+"_"+getOperationStr();
-        return  geneStr;
+        if (geneStrDirty || machineStrDirty || operationStrDirty) {
+            geneStr = getMachineStr() + "_" + getOperationStr();
+            geneStrDirty = false;
+        }
+        return geneStr;
     }
 
     private Integer gsOrls=0;
 
 
     public String  getMachineStr() {
-
-        machineStr=   Optional.ofNullable(machineSelection)
-                .orElse(Collections.emptyList())
-                .stream()
-                .map(String::valueOf) // Integer转String
-                .collect(Collectors.joining(","));
-       return machineStr;
+        if (machineStrDirty) {
+            machineStr = Optional.ofNullable(machineSelection)
+                    .orElse(Collections.emptyList())
+                    .stream()
+                    .map(String::valueOf)
+                    .collect(Collectors.joining(","));
+            machineStrDirty = false;
+            geneStrDirty = true;
+        }
+        return machineStr;
     }
 
     public String  getOperationStr() {
+        if (operationStrDirty) {
+            operationStr = Optional.ofNullable(operationSequencing)
+                    .orElse(Collections.emptyList())
+                    .stream()
+                    .map(String::valueOf)
+                    .collect(Collectors.joining(","));
+            operationStrDirty = false;
+            geneStrDirty = true;
+        }
+        return operationStr;
+    }
 
+    // 重写 setter 方法，在设置时标记为脏
+    public void setMachineSelection(List<Integer> machineSelection) {
+        this.machineSelection = machineSelection;
+        this.machineStrDirty = true;
+        this.geneStrDirty = true;
+    }
 
-        operationStr=   Optional.ofNullable(operationSequencing)
-                .orElse(Collections.emptyList())
-                .stream()
-                .map(String::valueOf) // Integer转String
-                .collect(Collectors.joining(","));
-        return  operationStr;
+    public void setOperationSequencing(List<Integer> operationSequencing) {
+        this.operationSequencing = operationSequencing;
+        this.operationStrDirty = true;
+        this.geneStrDirty = true;
     }
 
 
@@ -105,7 +131,7 @@ public class Chromosome {
 
     private  List<String> materialIds;
     /*
-    * 最早完工时间（最小化） 最小化总加工时间 最小总换型时间
+     * 最早完工时间（最小化） 最小化总加工时间 最小总换型时间
      */
     private double[] Objectives ; // 多目标值：[Makespan, TotalFlowTime, TotalChangeover, LoadStd, Delay]
     private double[] MaxObjectives ; //
@@ -113,8 +139,8 @@ public class Chromosome {
     private int Rank; // 非支配排序等级（1最优）
     private double CrowdingDistance =0; // 拥挤距离 越小越优
     /*
-    *(Objectives - min) / (max - min);
-    */
+     *(Objectives - min) / (max - min);
+     */
     private double[] WeightedObjectives;//越靠近1越优
     private double WeightedObjective =0; // 加权目标值（用于自定义权重）
 

src/main/java/com/aps/entity/Algorithm/ScheduleParams.java

@@ -15,7 +15,7 @@ public class ScheduleParams {
 
     // 基础参数（自适应调整的基准值）
     private static final int MIN_POPULATION_SIZE = 10;
-    private static final int MAX_POPULATION_SIZE = 50;
+    private static final int MAX_POPULATION_SIZE = 20;
     private static final int MIN_MAX_ITERATIONS = 50;
     private static final int MAX_MAX_ITERATIONS = 100;
     private static final float MIN_CROSSOVER_PROB = 0.6f;
@@ -172,10 +172,14 @@ public class ScheduleParams {
         // 1. 种群大小：50 ~ 500，随工序数线性增加
         populationSize = (int) Math.max(MIN_POPULATION_SIZE,
                 Math.min(MAX_POPULATION_SIZE, MIN_POPULATION_SIZE + totalOps * populationSizeCoeff));
+
+      int maxthead=  Runtime.getRuntime().availableProcessors() - 1;
+        populationSize= populationSize / maxthead*maxthead;
+
         // 确保偶数（方便交叉）
-        if (populationSize % 2 != 0) {
-            populationSize += 1;
-        }
+//        if (populationSize % 2 != 0) {
+//            populationSize += 1;
+//        }
 
         // 2. 最大迭代次数：50 ~ 200，随工序数线性减少
         maxIterations = (int) Math.max(MIN_MAX_ITERATIONS,

src/main/java/com/aps/entity/basic/GlobalParam.java

@@ -73,11 +73,11 @@ public class GlobalParam {
     public GlobalParam() {
         // 初始化默认目标值配置
         //完工时间、总流程时间、总换型时间、机器负载标准差、延迟时间
-        objectiveConfigs.add(new ObjectiveConfig(OBJECTIVE_MAKESPAN, true, 1, 0.6));
-        objectiveConfigs.add(new ObjectiveConfig(OBJECTIVE_FLOW_TIME, false, 2, 0.1));
+        objectiveConfigs.add(new ObjectiveConfig(OBJECTIVE_MAKESPAN, true, 1, 0.3));
+        objectiveConfigs.add(new ObjectiveConfig(OBJECTIVE_FLOW_TIME, true, 2, 0.1));
         objectiveConfigs.add(new ObjectiveConfig(OBJECTIVE_SETUP_TIME, true, 2, 0.1));
-        objectiveConfigs.add(new ObjectiveConfig(OBJECTIVE_MACHINE_LOAD, false, 3, 0.1));
-        objectiveConfigs.add(new ObjectiveConfig(OBJECTIVE_TARDINESS, true, 1, 0.3));
+        objectiveConfigs.add(new ObjectiveConfig(OBJECTIVE_MACHINE_LOAD, true, 1, 0.1));
+        objectiveConfigs.add(new ObjectiveConfig(OBJECTIVE_TARDINESS, true, 1, 0.6));
 
         objectiveConfigs.sort(Comparator.comparing((ObjectiveConfig op) -> op.getLevel()));
     }

src/main/java/com/aps/entity/basic/KpiTargetConfig.java

+package com.aps.entity.basic;
+
+/**
+ * 作者：佟礼
+ * 时间：2026-04-09
+ */
+public class KpiTargetConfig {
+}

src/main/java/com/aps/entity/basic/Order.java

@@ -156,6 +156,11 @@ public class Order {
      * 是否新创建，默认值：false
      */
     private boolean newCreate = false;
+
+    /**
+     * 是否新创建半成品，默认值：false
+     */
+    private boolean newSfCreate = false;
     
     /**
      * 是否创建BOM，默认值：false

src/main/java/com/aps/service/Algorithm/FitnessCalculator.java

@@ -21,8 +21,10 @@ public class FitnessCalculator {
 
         ArrayList<Double> list = new ArrayList<>();
         double fitness=0;
+        double total=0;
         int i=0;
         int level=-1;
+       double[] weightedObjectives=new double[chromosome.getObjectives().length];
         for (ObjectiveConfig config : param.getObjectiveConfigs()) {
             if( config.isEnabled()) {
 
@@ -65,7 +67,9 @@ public class FitnessCalculator {
                 if (!param.isPureNSGAIIMode()) {
                     val = val * config.getWeight();
                 }
+                weightedObjectives[i]=val;
                 fitness += val;
+                total+=val;
                 i++;
             }
         }
@@ -87,6 +91,8 @@ public class FitnessCalculator {
 //            fitness ≈ 0.01
 
         // 适应度值（越大越好）
+        chromosome.setFitness(total);
+        chromosome.setWeightedObjectives(weightedObjectives);
         return list.stream().mapToDouble(Double::doubleValue).toArray();
     }
 
@@ -147,7 +153,7 @@ public class FitnessCalculator {
         // 2. 计算每个个体与平均值的平方差之和
         float sumSqDiff = 0.0f;
         for (Chromosome chromosome : population) {
-            double diff = chromosome.getWeightedObjective() - avgFitness;
+            double diff = chromosome.getFitness() - avgFitness;
             sumSqDiff += diff * diff;
         }
 
@@ -155,6 +161,19 @@ public class FitnessCalculator {
         return (double) Math.sqrt(sumSqDiff / popSize);
     }
 
+    /**
+     * 比较两个染色体的优劣（基于fitnessLevel多层次比较）
+     */
+    public boolean isBetter(Chromosome c1, Chromosome c2) {
+        for (int i = 0; i < c1.getFitnessLevel().length; i++) {
+            double[] Fitness1 = c1.getFitnessLevel();
+            double[] Fitness2 = c2.getFitnessLevel();
+            if (Fitness1[i] > Fitness2[i]) {
+                return true;
+            }
+        }
+        return false;
+    }
 
 
 

src/main/java/com/aps/service/Algorithm/GeneticAlgorithm.java

@@ -425,7 +425,7 @@ public class GeneticAlgorithm {
 //            chromosome.setResultOld(new CopyOnWriteArrayList<>());
 //        }
 
-        decoder.decodeChromosomeWithCache(chromosome);
+        decoder.decodeChromosomeWithCache(chromosome,false);
         if (chromosome.getFitness() == 0) {
             chromosome.setFitness(_fitnessCalculator.calculateFitness(chromosome, _objectiveWeights));
         }

src/main/java/com/aps/service/Algorithm/GeneticOperations.java

@@ -25,6 +25,10 @@ public class GeneticOperations {
 
     private static ScheduleParams param;
 
+    public GeneticOperations() {
+
+    }
+
     public GeneticOperations(GlobalParam globalParam,List<Entry> _allOperations,ScheduleParams _param) {
         _GlobalParam=globalParam;
         allOperations = _allOperations;
@@ -424,10 +428,12 @@ public class GeneticOperations {
     public void DelOrder(Chromosome chromosome) {
         List<Entry> allOperations = chromosome.getAllOperations();
         List<GlobalOperationInfo> globalOpList=  chromosome.getGlobalOpList();
+        if(chromosome.getOrders()==null||chromosome.getOrders().size()==0)
+            return;
         List<Order> orders = chromosome.getOrders();
         List<Integer> OperationSequencing=  chromosome.getOperationSequencing();
         List<Integer> newoorderids= orders.stream()
-                .filter(t->t.isNewCreate())
+                .filter(t->t.isNewSfCreate())
                 .map(Order::getId)
                 .sorted(Comparator.reverseOrder())
                 .collect(Collectors.toList());

src/main/java/com/aps/service/Algorithm/Initialization.java

@@ -343,7 +343,7 @@ chromo.setOrders(new CopyOnWriteArrayList<>(orders));
     /**
      * 使用构造启发式算法生成初始种群
      */
-    public List<Chromosome> generateHeuristicInitialPopulation(ScheduleParams param, List<GlobalOperationInfo> globalOpList) {
+    public List<Chromosome> generateHeuristicInitialPopulation(ScheduleParams param) {
         List<Chromosome> population = new ArrayList<>();
         int populationSize = param.getPopulationSize();
         this.baseTime=param.getBaseTime();

src/main/java/com/aps/service/Algorithm/MaterialRequirementServicebf.java

@@ -894,7 +894,7 @@ public class MaterialRequirementServicebf {
                             childorder.setQuantity((int) orderMaterial.getQjQty());
                             childorder.setFinishOrderId(new ArrayList<>());
                             childorder.getFinishOrderId().add(forder.getId());
-                            childorder.setNewCreate(true);
+                            childorder.setNewSfCreate(true);
                             childorder.setTargetFinishedOperationId(new ArrayList<>());
                             childorder.getTargetFinishedOperationId().add(operation.getId());
                             childorder.setSerie(forder.getSerie());

src/main/java/com/aps/service/Algorithm/ParallelLocalSearch.java

-package com.aps.service.Algorithm;
-
-import com.aps.common.util.ProductionDeepCopyUtil;
-import com.aps.entity.Algorithm.*;
-import com.aps.entity.basic.Entry;
-import com.aps.entity.basic.GlobalParam;
-
-import java.util.ArrayList;
-import java.util.List;
-import java.util.concurrent.*;
-
-/**
- * 多种局部搜索算法并行
- */
-public class ParallelLocalSearch {
-    private final ExecutorService executor;
-    private GlobalParam globalParam;
-    private List<Entry> allOperations;
-    private List<GlobalOperationInfo> globalOpList;
-    private FitnessCalculator fitnessCalculator;
-    private ObjectiveWeights objectiveWeights;
-
-    public ParallelLocalSearch(GlobalParam globalParam, List<Entry> allOperations, List<GlobalOperationInfo> globalOpList, FitnessCalculator fitnessCalculator, ObjectiveWeights objectiveWeights) {
-        this.globalParam = globalParam;
-        this.allOperations = allOperations;
-        this.globalOpList = globalOpList;
-        this.fitnessCalculator = fitnessCalculator;
-        this.objectiveWeights = objectiveWeights;
-        this.executor = Executors.newFixedThreadPool(Runtime.getRuntime().availableProcessors());
-    }
-
-    /**
-     * 并行局部搜索
-     */
-    public Chromosome search(Chromosome chromosome, GeneticDecoder decoder, ScheduleParams param) {
-        List<Callable<Chromosome>> tasks = new ArrayList<>();
-
-        // 添加爬山法任务
-//        tasks.add(() -> {
-//            HillClimbing hillClimbing = new HillClimbing(globalParam, allOperations, globalOpList, fitnessCalculator, objectiveWeights);
-//            return hillClimbing.search(chromosome, decoder, param);
-//        });
-
-        // 添加变邻域搜索任务
-        tasks.add(() -> {
-            VariableNeighborhoodSearch vns = new VariableNeighborhoodSearch(globalParam, allOperations, globalOpList, fitnessCalculator, objectiveWeights);
-            return vns.search(chromosome, decoder, param);
-        });
-
-        // 添加模拟退火任务
-//        tasks.add(() -> {
-//            SimulatedAnnealing sa = new SimulatedAnnealing(globalParam, allOperations, globalOpList, fitnessCalculator, objectiveWeights);
-//            return sa.search(chromosome, decoder, param);
-//        });
-
-        // 执行所有任务
-        List<Chromosome> results = new ArrayList<>();
-        try {
-            List<Future<Chromosome>> futures = executor.invokeAll(tasks);
-            for (Future<Chromosome> future : futures) {
-                results.add(future.get());
-            }
-        } catch (InterruptedException | ExecutionException e) {
-            e.printStackTrace();
-        }
-
-        // 选择最优解
-        Chromosome best = chromosome;
-        for (Chromosome result : results) {
-            if (isBetter(result, best)) {
-                best = result;
-            }
-        }
-
-        return best;
-    }
-
-    /**
-     * 比较两个染色体的优劣
-     */
-    private boolean isBetter(Chromosome c1, Chromosome c2) {
-        return c1.getFitness() > c2.getFitness();
-    }
-
-    /**
-     * 关闭线程池
-     */
-    public void shutdown() {
-        executor.shutdown();
-    }
-}
\ No newline at end of file

src/main/java/com/aps/service/Algorithm/ScheduleOperationService.java

@@ -1885,7 +1885,7 @@ if(targetOp.getSequence()>1) {
 
 
 
-        decoder.decode(chromosome);
+        decoder.decode(chromosome,false);
 
         KpiCalculator kpiCalculator=new KpiCalculator(chromosome);
         kpiCalculator.calculatekpi();

src/main/java/com/aps/service/Algorithm/TabuSearchWithSA.java

-package com.aps.service.Algorithm;
-
-import com.aps.common.util.ProductionDeepCopyUtil;
-import com.aps.entity.Algorithm.*;
-import com.aps.entity.basic.Entry;
-import com.aps.entity.basic.GlobalParam;
-
-import java.util.*;
-
-/**
- * 禁忌搜索+模拟退火混合算法
- */
-public class TabuSearchWithSA {
-    private final Random rnd = new Random();
-    private GlobalParam globalParam;
-    private List<Entry> allOperations;
-    private List<GlobalOperationInfo> globalOpList;
-    private FitnessCalculator fitnessCalculator;
-    private ObjectiveWeights objectiveWeights;
-
-    // 禁忌表
-    private List<Chromosome> tabuList;
-    private int tabuListSize = 50;
-
-    public TabuSearchWithSA(GlobalParam globalParam, List<Entry> allOperations, List<GlobalOperationInfo> globalOpList, FitnessCalculator fitnessCalculator, ObjectiveWeights objectiveWeights) {
-        this.globalParam = globalParam;
-        this.allOperations = allOperations;
-        this.globalOpList = globalOpList;
-        this.fitnessCalculator = fitnessCalculator;
-        this.objectiveWeights = objectiveWeights;
-        this.tabuList = new ArrayList<>();
-    }
-
-    /**
-     * 禁忌搜索+模拟退火混合搜索
-     */
-    public Chromosome search(Chromosome chromosome, GeneticDecoder decoder, ScheduleParams param) {
-        Chromosome current = ProductionDeepCopyUtil.deepCopy(chromosome, Chromosome.class);
-        Chromosome best = ProductionDeepCopyUtil.deepCopy(chromosome, Chromosome.class);
-
-        // 初始化温度
-        double temperature = 100.0;
-        double coolingRate = 0.95;
-        int iterations = 0;
-        int maxIterations = 1000;
-        int noImprovementCount = 0;
-        int maxNoImprovement = 100;
-
-        while (iterations < maxIterations && noImprovementCount < maxNoImprovement) {
-            // 生成邻域解
-            List<Chromosome> neighbors = generateNeighbors(current);
-
-            // 过滤禁忌解
-            List<Chromosome> validNeighbors = filterTabuSolutions(neighbors);
-
-            // 评估所有邻域解
-            Chromosome bestNeighbor = null;
-            double bestNeighborFitness = Double.NEGATIVE_INFINITY;
-
-            for (Chromosome neighbor : validNeighbors) {
-                decode(decoder, neighbor, param);
-                if (neighbor.getFitness() > bestNeighborFitness) {
-                    bestNeighborFitness = neighbor.getFitness();
-                    bestNeighbor = neighbor;
-                }
-            }
-
-            if (bestNeighbor != null) {
-                // 计算能量差
-                decode(decoder, current, param);
-                double energyDifference = bestNeighbor.getFitness() - current.getFitness();
-
-                // 结合模拟退火的概率接受机制
-                if (energyDifference > 0 || rnd.nextDouble() < Math.exp(energyDifference / temperature)) {
-                    // 更新当前解
-                    current = bestNeighbor;
-
-                    // 更新禁忌表
-                    addToTabuList(current);
-
-                    // 更新最优解
-                    if (isBetter(current, best)) {
-                        best = current;
-                        noImprovementCount = 0;
-                    } else {
-                        noImprovementCount++;
-                    }
-                }
-            }
-
-            // 降温
-            temperature *= coolingRate;
-            iterations++;
-        }
-
-        return best;
-    }
-
-    /**
-     * 生成邻域解
-     */
-    private List<Chromosome> generateNeighbors(Chromosome chromosome) {
-        List<Chromosome> neighbors = new ArrayList<>();
-
-        // 生成多个邻域解
-        for (int i = 0; i < 10; i++) {
-            int neighborType = rnd.nextInt(4);
-            switch (neighborType) {
-                case 0:
-                    neighbors.add(generateSwapNeighbor(chromosome));
-                    break;
-                case 1:
-                    neighbors.add(generateReverseNeighbor(chromosome));
-                    break;
-                case 2:
-                    neighbors.add(generateInsertNeighbor(chromosome));
-                    break;
-                case 3:
-                    neighbors.add(generateMachineChangeNeighbor(chromosome));
-                    break;
-            }
-        }
-
-        return neighbors;
-    }
-
-    /**
-     * 过滤禁忌解
-     */
-    private List<Chromosome> filterTabuSolutions(List<Chromosome> neighbors) {
-        List<Chromosome> validNeighbors = new ArrayList<>();
-
-        for (Chromosome neighbor : neighbors) {
-            if (!isTabu(neighbor)) {
-                validNeighbors.add(neighbor);
-            }
-        }
-
-        // 如果没有有效邻域解，返回所有邻域解
-        if (validNeighbors.isEmpty()) {
-            return neighbors;
-        }
-
-        return validNeighbors;
-    }
-
-    /**
-     * 检查解是否在禁忌表中
-     */
-    private boolean isTabu(Chromosome chromosome) {
-        for (Chromosome tabuChromosome : tabuList) {
-            if (chromosome.getGeneStr().equals(tabuChromosome.getGeneStr())) {
-                return true;
-            }
-        }
-        return false;
-    }
-
-    /**
-     * 添加解到禁忌表
-     */
-    private void addToTabuList(Chromosome chromosome) {
-        tabuList.add(chromosome);
-        if (tabuList.size() > tabuListSize) {
-            tabuList.remove(0);
-        }
-    }
-
-    /**
-     * 生成交换邻域解
-     */
-    private Chromosome generateSwapNeighbor(Chromosome chromosome) {
-        Chromosome neighbor = ProductionDeepCopyUtil.deepCopy(chromosome, Chromosome.class);
-        List<Integer> os = neighbor.getOperationSequencing();
-        if (os.size() >= 2) {
-            int idx1 = rnd.nextInt(os.size());
-            int idx2 = rnd.nextInt(os.size());
-            while (idx2 == idx1) {
-                idx2 = rnd.nextInt(os.size());
-            }
-            Collections.swap(os, idx1, idx2);
-            neighbor.setOperationSequencing(os);
-        }
-        return neighbor;
-    }
-
-    /**
-     * 生成反转邻域解
-     */
-    private Chromosome generateReverseNeighbor(Chromosome chromosome) {
-        Chromosome neighbor = ProductionDeepCopyUtil.deepCopy(chromosome, Chromosome.class);
-        List<Integer> os = neighbor.getOperationSequencing();
-        if (os.size() >= 2) {
-            int start = rnd.nextInt(os.size());
-            int end = rnd.nextInt(os.size());
-            while (end <= start) {
-                end = rnd.nextInt(os.size());
-            }
-            Collections.reverse(os.subList(start, end + 1));
-            neighbor.setOperationSequencing(os);
-        }
-        return neighbor;
-    }
-
-    /**
-     * 生成插入邻域解
-     */
-    private Chromosome generateInsertNeighbor(Chromosome chromosome) {
-        Chromosome neighbor = ProductionDeepCopyUtil.deepCopy(chromosome, Chromosome.class);
-        List<Integer> os = neighbor.getOperationSequencing();
-        if (os.size() >= 2) {
-            int idx1 = rnd.nextInt(os.size());
-            int idx2 = rnd.nextInt(os.size());
-            while (idx2 == idx1) {
-                idx2 = rnd.nextInt(os.size());
-            }
-            int value = os.remove(idx1);
-            os.add(idx2, value);
-            neighbor.setOperationSequencing(os);
-        }
-        return neighbor;
-    }
-
-    /**
-     * 生成机器选择邻域解
-     */
-    private Chromosome generateMachineChangeNeighbor(Chromosome chromosome) {
-        Chromosome neighbor = ProductionDeepCopyUtil.deepCopy(chromosome, Chromosome.class);
-        List<Integer> ms = neighbor.getMachineSelection();
-        if (!ms.isEmpty()) {
-            int idx = rnd.nextInt(ms.size());
-            GlobalOperationInfo globalOp = globalOpList.get(idx);
-            Entry op = globalOp.getOp();
-
-            if (op.getMachineOptions().size() > 1) {
-                int currentMachineSeq = ms.get(idx);
-                List<Integer> availableMachines = new ArrayList<>();
-                for (int i = 1; i <= op.getMachineOptions().size(); i++) {
-                    if (i != currentMachineSeq) {
-                        availableMachines.add(i);
-                    }
-                }
-
-                if (!availableMachines.isEmpty()) {
-                    int newMachineSeq = availableMachines.get(rnd.nextInt(availableMachines.size()));
-                    ms.set(idx, newMachineSeq);
-                    neighbor.setMachineSelection(ms);
-                }
-            }
-        }
-        return neighbor;
-    }
-
-    /**
-     * 解码染色体
-     */
-    private void decode(GeneticDecoder decoder, Chromosome chromosome, ScheduleParams param) {
-        chromosome.setResult(new java.util.concurrent.CopyOnWriteArrayList<>());
-        decoder.decodeChromosomeWithCache(chromosome);
-        if (chromosome.getFitness() == 0) {
-            chromosome.setFitness(fitnessCalculator.calculateFitness(chromosome, objectiveWeights));
-        }
-    }
-
-    /**
-     * 比较两个染色体的优劣
-     */
-    private boolean isBetter(Chromosome c1, Chromosome c2) {
-        return c1.getFitness() > c2.getFitness();
-    }
-}
\ No newline at end of file

src/main/java/com/aps/service/plan/PlanResultService.java

@@ -222,7 +222,7 @@ public class PlanResultService {
             lockedOrderProcessorService.markLockedOrdersOccupiedTime(machines, timeConfig.getBaseTime());
 
             // 5. 执行调度算法
-            GeneticAlgorithm scheduler =new GeneticAlgorithm(globalParam,machines,orders,Materials1,materialIds,machineScheduler,entryRel,materialRequirementService,_sceneService,SceneId); //new GeneticAlgorithm(products, machines, orders, machineScheduler);
+            HybridAlgorithm scheduler =new HybridAlgorithm(globalParam,machines,orders,Materials1,materialIds,machineScheduler,entryRel,materialRequirementService,_sceneService,SceneId); //new GeneticAlgorithm(products, machines, orders, machineScheduler);
             param.initAdaptiveParams(entrys.size());
             double[] customWeights = new double[] { 0.4, 0.1, 0.1, 0.1, 0.3 }; // 延迟时间权重提升到0.5
             //完工时间、总流程时间、总换型时间、机器负载标准差、延迟时间
@@ -238,7 +238,7 @@ public class PlanResultService {
 
             _sceneService.saveChromosomeToFile(chromosome, SceneId);
 
-            WriteScheduleSummary(chromosome);
+          //  WriteScheduleSummary(chromosome);
 
             return chromosome;
 

src/main/java/com/aps/service/plan/SceneService.java

@@ -132,7 +132,7 @@ public class SceneService {
         try {
             ObjectMapper objectMapper = createObjectMapper();
 
-            SceneChromsome sceneChromsome=(SceneChromsome)redisUtils.get("SceneId."+sceneId);
+            SceneChromsome sceneChromsome=null;//(SceneChromsome)redisUtils.get("SceneId."+sceneId);
             if(sceneChromsome==null)
             {
                 sceneChromsome=new SceneChromsome();
@@ -163,7 +163,7 @@ public class SceneService {
             sceneChromsome.getSceneDetails().add(sceneDetail);
 
 
-            redisUtils.set("SceneId."+sceneId,sceneChromsome);
+         //   redisUtils.set("SceneId."+sceneId,sceneChromsome);
 
             File file = getChromosomeFile(sceneId,sceneChromsome.getVersion().toString());
 

src/test/java/com/aps/demo/PlanResultServiceTest.java

@@ -39,7 +39,8 @@ public class PlanResultServiceTest {
       //  TestSortService  sortService=new TestSortService();
      //  sortService.test1();
        // nsgaiiUtils.Test();
-      planResultService.execute2("0428340BB4F540938F1FB5599F03E8A4");//2000
+        planResultService.execute2("08B1D87FE1B84ECDBAC2E546DDB6FB81");//2000
+     // planResultService.execute2("0428340BB4F540938F1FB5599F03E8A4");//2000
        // planResultService.execute2("C8B533BD8944405B9A2F8823C575C204");//500
        // planResultService.execute2("EFDD34E4B5BC434BAEAE6A84DFCD4E7B");//20
       //  planResultService.execute2("00E0C5D3E4AD4F36B56C39395906618D");