MP-调整目标值为最大化，增加kpi 总需求松弛, 增加固定第0层，包含kpi总需求松弛

src/main/java/com/aps/controller/MacroPlannerResultController.java

@@ -1024,7 +1024,7 @@ public class MacroPlannerResultController {
                 entryMap.put("name", e.name);
                 entryMap.put("rawValue", String.format("%.2f", e.rawValue));
                 entryMap.put("weight", String.format("%.1f", e.weight));
-                entryMap.put("penalty", String.format("%.2f", e.penalty));
+                entryMap.put("contribution", String.format("%.2f", e.contribution));
                 kpiList.add(entryMap);
             }
             kpiData.put("entries", kpiList);

src/main/java/com/aps/macroplanner/MacroPlannerOptimizer.java

@@ -286,7 +286,7 @@ public class MacroPlannerOptimizer {
         // ========== 1. 前置参数校验 ==========
         List<KpiSetting> w = data.getKpiSettings();
         List<StrategyLevel> levels=new ArrayList<>();
-        if (w == null) {
+        if (w == null||w.size()==0) {
             levels = defineLevels(data.getKpiWeights());
         }else {
             levels = getKpiLevels(w);
@@ -342,16 +342,18 @@ public class MacroPlannerOptimizer {
                 double bestBound = model.getSolver().objective().bestBound();
                 writeLog("  SCIP Status        : %s%n", status);
                 writeLog("  Solving Time (sec) : %.2f%n", levelElapsedMs / 1000.0);
-                writeLog("  Primal Bound       : %+.6e%n", optimalValue);
+                writeLog("  Goal Score       : %+.6e%n", optimalValue);
                 writeLog("  Best Bound       : %+.6e%n", bestBound);
+
                 double gap = Math.abs(optimalValue - bestBound) / Math.abs(optimalValue) * 100;
                 writeLog("gap：%.2f", gap);
                 // 输出当前层各KPI值
                 for (StrategyLevel.KPIEntry kpi : level.getKpis()) {
                     double kpiValue = kpi.variable.solutionValue();
-                    double penalty = kpi.effectiveCoefficient() * kpiValue;
-                    writeLog("    %s: %.2f (系数=%.1f, 惩罚=%.2f)%n",
-                            kpi.name, kpiValue, kpi.effectiveCoefficient(), penalty);
+                    double contribution = kpi.effectiveCoefficient() * kpiValue;
+
+                    System.out.printf("    %s: %.2f (系数=%+.1f, 得分贡献=%+.2f)%n",
+                            kpi.name, kpiValue, kpi.effectiveCoefficient(), contribution);
                 }
 
                 levelResults.add(new LevelResult(level, optimalValue, status));
@@ -431,14 +433,19 @@ public class MacroPlannerOptimizer {
     private List<StrategyLevel> defineLevels(KPIWeights w) {
         List<StrategyLevel> levels = new ArrayList<>();
 
+        // === Level 0: 需求满足 (最高优先级, 严格分层, slack=0%) ===
+        StrategyLevel l0 = new StrategyLevel(0, "需求松弛", 0.0);
+        l0.addKPI("TotalSlack","需求松弛", model.getTotalSlack(), 1);
+        levels.add(l0);
+
         // === Level 1: 需求满足 (最高优先级, 严格分层, slack=0%) ===
         StrategyLevel l1 = new StrategyLevel(1, "需求满足", 0.0);
-        l1.addKPI(KpiLib.Fulfillment.getEn(),KpiLib.Fulfillment.getCn(), model.getTotalFulfillment(), w.getFulfillmentWeight());
+        l1.addKPI(KpiLib.Fulfillment.getEn(),KpiLib.Fulfillment.getCn(), model.getTotalFulfillment(), w.getFulfillmentWeight(),true);
         levels.add(l1);
 
         // === Level 2: 产能约束 (物理硬约束, 严格分层, slack=0%) ===
         StrategyLevel l2 = new StrategyLevel(2, "产能约束", 0.0);
-        l2.addKPI(KpiLib.UnitCapacity.getEn(),KpiLib.Fulfillment.getCn(), model.getTotalUnitCapacity(), w.getUnitCapacityWeight());
+        l2.addKPI(KpiLib.UnitCapacity.getEn(),KpiLib.UnitCapacity.getCn(), model.getTotalUnitCapacity(), w.getUnitCapacityWeight());
         levels.add(l2);
 
         // === Level 3: 业务KPI (允许 5% 退化, slack=5%) ===
@@ -472,7 +479,10 @@ public class MacroPlannerOptimizer {
                         TreeMap::new,
                         Collectors.toList()
                 ));
-
+        // === Level 0: 需求满足 (最高优先级, 严格分层, slack=0%) ===
+        StrategyLevel l0 = new StrategyLevel(0, "需求松弛", 0.0);
+        l0.addKPI("TotalSlack","需求松弛", model.getTotalSlack(), 1);
+        levels.add(l0);
         for (Map.Entry<Integer, List<KpiSetting>> entry : groupByLevelMap.entrySet()) {
             Integer currentLevel = entry.getKey();
             List<KpiSetting> kpiGroup = entry.getValue();
@@ -480,7 +490,7 @@ public class MacroPlannerOptimizer {
             // 遍历当前分组里面每一个KPI
             for (KpiSetting kpi : kpiGroup) {
 
-                level.addKPI(kpi.code, kpi.name, model.getKpi(kpi.code), kpi.weight);
+                level.addKPI(kpi.code, kpi.name, model.getKpi(kpi.code), kpi.weight,KpiLib.ofEn(kpi.code).getIsBenefit());
 
             }
 

src/main/java/com/aps/macroplanner/constraint/KpiAggregator.java

@@ -38,8 +38,12 @@ public class KpiAggregator {
     public static void build(MacroPlannerModel model, TestDataBuilder data) {
         double inf = MPSolver.infinity();
 
-        // TotalFulfillment = Σ DemandSlack
+        // TotalFulfillment = Σ SalesDemandQty (Quintiq fulfillment bonus KPI)
         model.setTotalFulfillment(createSumKpi(model, "TotalFulfillment",
+                model.getSalesDemandQtyVars()));
+
+        // TotalSlack = Σ DemandSlack (Quintiq Slack KPI, 高优先级惩罚)
+        model.setTotalSlack(createSumKpi(model, "TotalSlack",
                 model.getDemandSlackVars()));
 
         // TotalLotSize = Σ PTLotSizeOver + Σ PTLotSizeUnder
@@ -66,10 +70,16 @@ public class KpiAggregator {
         model.setTotalUnitCapacity(createSumKpi(model, "TotalUnitCapacity",
                 model.getCapacityOverloadedVars()));
 
+        // TotalMinimumUnitCapacity = Σ CapacityNotMet (Quintiq 最小产能未满足 KPI)
+        model.setTotalMinimumUnitCapacity(createSumKpi(model, "TotalMinUnitCapacity",
+                model.getCapacityNotMetVars()));
+
         // TotalSupplyTarget = Σ SupplyTargetQtyUnder
         model.setTotalSupplyTarget(createSumKpi(model, "TotalSupplyTarget",
                 model.getSupplyTargetQtyUnderVars()));
 
+
+
         // TotalMinSupply = Σ MinSupplyQtyUnder
         model.setTotalMinSupply(createSumKpi(model, "TotalMinSupply",
                 model.getMinSupplyQtyUnderVars()));

src/main/java/com/aps/macroplanner/model/MacroPlannerModel.java

@@ -80,12 +80,19 @@ public class MacroPlannerModel {
     private final Map<String, MPVariable> ptLotSizeUnderVars = new HashMap<>();
 
     // ==================== KPI 汇总变量 ====================
+
+    private MPVariable totalSlack;
+
     private MPVariable totalFulfillment;
+
+
     private MPVariable totalLotSize;
     private MPVariable totalMaxInventoryLevel;
     private MPVariable totalMinInventoryLevel;
     private MPVariable totalTargetInvLevel;
     private MPVariable totalUnitCapacity;
+    private MPVariable totalMinimumUnitCapacity;
+
     private MPVariable totalSupplyTarget;
     private MPVariable totalMinSupply;
     private MPVariable totalMaxSupply;
@@ -123,6 +130,7 @@ public class MacroPlannerModel {
     }
 
     // ==================== KPI 变量 setter (由 KpiAggregator 调用) ====================
+    public void setTotalSlack(MPVariable v) { this.totalSlack = v; }
 
     public void setTotalFulfillment(MPVariable v) { this.totalFulfillment = v; }
     public void setTotalLotSize(MPVariable v) { this.totalLotSize = v; }
@@ -130,6 +138,9 @@ public class MacroPlannerModel {
     public void setTotalMinInventoryLevel(MPVariable v) { this.totalMinInventoryLevel = v; }
     public void setTotalTargetInvLevel(MPVariable v) { this.totalTargetInvLevel = v; }
     public void setTotalUnitCapacity(MPVariable v) { this.totalUnitCapacity = v; }
+
+    public void setTotalMinimumUnitCapacity(MPVariable v) { this.totalMinimumUnitCapacity = v; }
+
     public void setTotalSupplyTarget(MPVariable v) { this.totalSupplyTarget = v; }
     public void setTotalMinSupply(MPVariable v) { this.totalMinSupply = v; }
     public void setTotalMaxSupply(MPVariable v) { this.totalMaxSupply = v; }
@@ -150,6 +161,8 @@ public class MacroPlannerModel {
     public Map<String, MPVariable> getDemandFulfillmentVars() { return demandFulfillmentVars; }
     public Map<String, MPVariable> getCapacityOverloadedVars() { return capacityOverloadedVars; }
     public Map<String, MPVariable> getCapacityNotMetVars() { return capacityNotMetVars; }
+
+
     public Map<String, MPVariable> getMinInvQtyUnderVars() { return minInvQtyUnderVars; }
     public Map<String, MPVariable> getMaxInvQtyOverVars() { return maxInvQtyOverVars; }
     public Map<String, MPVariable> getInvQtyUnderTargetVars() { return invQtyUnderTargetVars; }
@@ -159,12 +172,16 @@ public class MacroPlannerModel {
     public Map<String, MPVariable> getPtLotSizeOverVars() { return ptLotSizeOverVars; }
     public Map<String, MPVariable> getPtLotSizeUnderVars() { return ptLotSizeUnderVars; }
 
+    public MPVariable getTotalSlack() { return totalSlack; }
     public MPVariable getTotalFulfillment() { return totalFulfillment; }
     public MPVariable getTotalLotSize() { return totalLotSize; }
     public MPVariable getTotalMaxInventoryLevel() { return totalMaxInventoryLevel; }
     public MPVariable getTotalMinInventoryLevel() { return totalMinInventoryLevel; }
     public MPVariable getTotalTargetInvLevel() { return totalTargetInvLevel; }
     public MPVariable getTotalUnitCapacity() { return totalUnitCapacity; }
+
+    public MPVariable getTotalMinimumUnitCapacity() { return totalMinimumUnitCapacity; }
+
     public MPVariable getTotalSupplyTarget() { return totalSupplyTarget; }
     public MPVariable getTotalMinSupply() { return totalMinSupply; }
     public MPVariable getTotalMaxSupply() { return totalMaxSupply; }
@@ -183,6 +200,9 @@ public class MacroPlannerModel {
             case UnitCapacity:
                 kpivar = totalUnitCapacity;
                 break;
+            case MinUnitCapacity:
+                kpivar = totalMinimumUnitCapacity;
+                break;
             case LotSize:
                 kpivar = totalLotSize;
                 break;

src/main/java/com/aps/macroplanner/objective/KpiLib.java

@@ -9,23 +9,28 @@ import java.util.stream.Collectors;
  * 时间：2026-09-22
  */
 public enum KpiLib {
-    Fulfillment("需求满足"),
-    UnitCapacity("产能"),
-    LotSize("批次"),
-    TargetInvLevel("目标库存"),
-    SupplyTarget("供应目标"),
-    SalesDemandPriority("销售优先级"),
-    MaxInventoryLevel("最大库存"),
-    MinInventoryLevel("最小库存"),
-    MinSupply("最小供应"),
-    MaxSupply("最大供应");
+    Fulfillment("需求满足",true),
+    UnitCapacity("产能",false),
+    MinUnitCapacity("最小化产能",false),
+    LotSize("批次",false),
+    TargetInvLevel("目标库存",false),
+    SupplyTarget("供应目标",false),
+    SalesDemandPriority("销售优先级",false),
+    MaxInventoryLevel("最大库存",false),
+    MinInventoryLevel("最小库存",false),
+    MinSupply("最小供应",false),
+    MaxSupply("最大供应",false);
 
     private final String en;
     private final String cn;
 
-    KpiLib(String cn) {
+    /** 是否为收益 KPI（越大越好）。 */
+    public final boolean isBenefit;
+
+    KpiLib(String cn,boolean isBenefit) {
         this.en = this.name();
         this.cn = cn;
+        this.isBenefit=isBenefit;
     }
 
     public String getEn() {
@@ -36,6 +41,10 @@ public enum KpiLib {
         return cn;
     }
 
+    public boolean getIsBenefit() {
+        return isBenefit;
+    }
+
     /**
      * 转为 Map<英文编码,中文名称>，用于批量翻译、表头转换
      */

src/main/java/com/aps/macroplanner/objective/ObjectiveBuilder.java

@@ -168,18 +168,18 @@ public class ObjectiveBuilder {
         for (StrategyLevel.KPIEntry kpi : level.getKpis()) {
             objective.setCoefficient(kpi.variable, kpi.effectiveCoefficient());
         }
-        objective.setMinimization();
+        objective.setMaximization();
     }
 
     /**
-     * 添加层级边界约束 — 限制上层目标值不超过最优值 × (1 + slack)。
+     * 添加层级边界约束 — 限制上层得分不低于最优值减去允许松弛。
      *
      * <p>该约束确保在求解下层 KPI 时, 上层 KPI 不会退化超过允许范围。
      * 对应 Quintiq 中 StrategyLevel 的 HierarchicalSolver 约束。</p>
      *
      * <h3>数学公式</h3>
      * <pre>
-     *   Σ (effectiveCoeff × KPI_variable) ≤ optimalValue + |optimalValue| × relativeGoalSlack
+     *   Σ (effectiveCoeff × KPI_variable) ≥ optimalValue - |optimalValue × relativeGoalSlack|
      * </pre>
      *
      * @param model        模型容器
@@ -192,10 +192,10 @@ public class ObjectiveBuilder {
         if (level.getRelativeGoalSlack() < 0.0) return; // 负松弛表示不约束
 
         MPSolver solver = model.getSolver();
-        double upperBound = computeUpperBound(optimalValue, level.getRelativeGoalSlack());
+        double lowerBound = optimalValue - Math.abs(optimalValue * level.getRelativeGoalSlack());
 
         MPConstraint bound = solver.makeConstraint(
-                -MPSolver.infinity(), upperBound,
+                lowerBound, MPSolver.infinity(),
                 "HierLevel" + level.getLevel() + "_Bound");
 
         for (StrategyLevel.KPIEntry kpi : level.getKpis()) {

src/main/java/com/aps/macroplanner/objective/StrategyLevel.java

@@ -60,8 +60,8 @@ public class StrategyLevel {
         /** 该 KPI 在当前层级内的权重 */
         public final double weight;
 
-        /** 是否为负向 KPI (越小越好 = 正常惩罚项; false = 正常惩罚项) */
-        public final boolean isNegative;
+        /** 是否为收益 KPI（越大越好）。 */
+        public final boolean isBenefit;
 
         /** 编号 */
         public final String code;
@@ -69,20 +69,20 @@ public class StrategyLevel {
         /** KPI 名称 (用于日志) */
         public final String name;
 
-        public KPIEntry(String code,String name, MPVariable variable, double weight, boolean isNegative) {
+        public KPIEntry(String code,String name, MPVariable variable, double weight, boolean isBenefit) {
             this.code = code;
             this.name = name;
             this.variable = variable;
             this.weight = weight;
-            this.isNegative = isNegative;
+            this.isBenefit = isBenefit;
         }
 
         /**
          * 计算该 KPI 在目标函数中的实际系数。
-         * 负向 KPI (如 SalesDemandPriority) 使用负系数实现最大化。
+         * 收益 KPI 使用正系数；惩罚 KPI 使用负系数。
          */
         public double effectiveCoefficient() {
-            return isNegative ? -weight : weight;
+            return isBenefit ? weight : -weight;
         }
     }
 
@@ -116,11 +116,11 @@ public class StrategyLevel {
      * @param name       KPI 名称
      * @param variable   KPI 汇总变量
      * @param weight     权重 (0 = 跳过)
-     * @param isNegative 是否为负向 KPI (true = 最大化, 使用负系数)
+     * @param isBenefit 是否为收益 KPI（true = 最大化得分中的正系数）
      */
-    public void addKPI(String code, String name, MPVariable variable, double weight, boolean isNegative) {
+    public void addKPI(String code,String name, MPVariable variable, double weight, boolean isBenefit) {
         if (weight > 0.0 && variable != null) {
-            kpis.add(new KPIEntry(code,name, variable, weight, isNegative));
+            kpis.add(new KPIEntry(code,name, variable, weight, isBenefit));
         }
     }
 

src/main/java/com/aps/macroplanner/output/ResultWriter.java

@@ -535,7 +535,7 @@ public class ResultWriter {
 
         // KPI + 统计
         writeLog("Kpi");
-       // result.setKpis(buildKpis());
+        result.setKpis(buildKpis());
         //  result.setStatistics(buildStatistics());
 
         return result;
@@ -1491,6 +1491,8 @@ public class ResultWriter {
         double objValue = model.getSolver().objective().value();
         kr.setObjectiveValue(objValue);
 
+
+
         kr.addEntry("需求缺口(Fulfillment)",
                 model.getTotalFulfillment().solutionValue(),
                 w.getFulfillmentWeight(), false);
@@ -1715,7 +1717,7 @@ public class ResultWriter {
                     .key("name").val(e.name)
                     .key("rawValue").val(e.rawValue)
                     .key("weight").val(e.weight)
-                    .key("penalty").val(e.penalty)
+                    .key("contribution").val(e.contribution)
                     .key("isBenefit").val(e.isBenefit)
                     .endObj();
         }

src/main/java/com/aps/macroplanner/output/SolutionPrinter.java

@@ -693,37 +693,37 @@ public class SolutionPrinter {
 
         // 计算并输出加权总惩罚 (等价于单目标函数值)
         writeLog("");
-        writeLog("--- 最终 KPI 值 (加权总惩罚) ---");
-        double fulfillment = model.getTotalFulfillment().solutionValue();
-        double lotSize = model.getTotalLotSize().solutionValue();
-        double maxInv = model.getTotalMaxInventoryLevel().solutionValue();
-        double minInv = model.getTotalMinInventoryLevel().solutionValue();
-        double targetInv = model.getTotalTargetInvLevel().solutionValue();
-        double capacity = model.getTotalUnitCapacity().solutionValue();
-        double supplyTarget = model.getTotalSupplyTarget().solutionValue();
-        double minSupply = model.getTotalMinSupply().solutionValue();
-        double maxSupply = model.getTotalMaxSupply().solutionValue();
-        double salesPriority = model.getTotalSalesDemandPriority().solutionValue();
-
-        double totalPenalty = fulfillment * weights.getOrDefault(KpiLib.Fulfillment.getEn(),0d)
-                + lotSize * weights.getOrDefault(KpiLib.LotSize.getEn(),0d)
-                + maxInv * weights.getOrDefault(KpiLib.MinInventoryLevel.getEn(),0d)
-                + minInv * weights.getOrDefault(KpiLib.MinInventoryLevel.getEn(),0d)
-                + targetInv * weights.getOrDefault(KpiLib.TargetInvLevel.getEn(),0d)
-                + capacity * weights.getOrDefault(KpiLib.UnitCapacity.getEn(),0d)
-                + supplyTarget * weights.getOrDefault(KpiLib.SupplyTarget.getEn(),0d)
-                + minSupply * weights.getOrDefault(KpiLib.MinSupply.getEn(),0d)
-                + maxSupply * weights.getOrDefault(KpiLib.MaxSupply.getEn(),0d)
-                - salesPriority * weights.getOrDefault(KpiLib.SalesDemandPriority.getEn(),0d);
-
-        writeLog("  加权总惩罚: %.2f", totalPenalty);
+      //  writeLog("--- 最终 KPI 值 (加权总惩罚) ---");
+//        double fulfillment = model.getTotalFulfillment().solutionValue();
+//        double lotSize = model.getTotalLotSize().solutionValue();
+//        double maxInv = model.getTotalMaxInventoryLevel().solutionValue();
+//        double minInv = model.getTotalMinInventoryLevel().solutionValue();
+//        double targetInv = model.getTotalTargetInvLevel().solutionValue();
+//        double capacity = model.getTotalUnitCapacity().solutionValue();
+//        double supplyTarget = model.getTotalSupplyTarget().solutionValue();
+//        double minSupply = model.getTotalMinSupply().solutionValue();
+//        double maxSupply = model.getTotalMaxSupply().solutionValue();
+//        double salesPriority = model.getTotalSalesDemandPriority().solutionValue();
+
+//        double totalPenalty = fulfillment * weights.getOrDefault(KpiLib.Fulfillment.getEn(),0d)
+//                + lotSize * weights.getOrDefault(KpiLib.LotSize.getEn(),0d)
+//                + maxInv * weights.getOrDefault(KpiLib.MinInventoryLevel.getEn(),0d)
+//                + minInv * weights.getOrDefault(KpiLib.MinInventoryLevel.getEn(),0d)
+//                + targetInv * weights.getOrDefault(KpiLib.TargetInvLevel.getEn(),0d)
+//                + capacity * weights.getOrDefault(KpiLib.UnitCapacity.getEn(),0d)
+//                + supplyTarget * weights.getOrDefault(KpiLib.SupplyTarget.getEn(),0d)
+//                + minSupply * weights.getOrDefault(KpiLib.MinSupply.getEn(),0d)
+//                + maxSupply * weights.getOrDefault(KpiLib.MaxSupply.getEn(),0d)
+//                - salesPriority * weights.getOrDefault(KpiLib.SalesDemandPriority.getEn(),0d);
+//
+//        writeLog("  总kpi: %.2f", totalPenalty);
 
         for (Map.Entry<String, Double> entry : weights.entrySet()) {
             String key = entry.getKey();
             Double weight = entry.getValue();
             KpiLib kpi = KpiLib.ofEn(key);
             double val= model.getKpi(key).solutionValue();
-            writeLog("  %s:   %.2f (权重%.0f × %.2f)",
+            writeLog("  %s:   %.2f (%.0f × %.2f)",
                     kpi.getCn(),val * weight, val, weight);
         }
 

src/main/java/com/aps/macroplanner/output/dto/KpiResult.java

@@ -24,8 +24,8 @@ public class KpiResult {
         public double rawValue;
         /** 权重 */
         public double weight;
-        /** 加权惩罚 = rawValue × weight */
-        public double penalty;
+        /** 得分贡献 = rawValue × weight（收益项为正, 惩罚项为负） */
+        public double contribution;
         /** 是否为收益项 (越大越好, 正系数) */
         public boolean isBenefit;
     }
@@ -43,7 +43,7 @@ public class KpiResult {
         e.rawValue = rawValue;
         e.weight = weight;
         e.isBenefit = isBenefit;
-        e.penalty = isBenefit ? -rawValue * weight : rawValue * weight;
+        e.contribution = isBenefit ? rawValue * weight : -rawValue * weight;
         entries.add(e);
     }
 }
\ No newline at end of file