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cpte-boot-module/cpte-module-wms/src/main/java/org/cpte/modules/conveyorLine/service/processor/ScanTrayProcessor.java

@@ -26,10 +26,8 @@ import org.cpte.modules.receive.mapper.AsnMapper;
 import org.springframework.beans.factory.annotation.Autowired;
 import org.springframework.stereotype.Service;
 
-import java.util.Collections;
+import java.util.*;
-import java.util.Comparator;
+import java.util.stream.Collectors;
-import java.util.List;
-import java.util.Set;
 
 /**
  * 扫描托盘处理
@@ -204,14 +202,16 @@ public class ScanTrayProcessor {
             //2.获取所有可用库位
             availablePoints = pointMapper.queryPoints(null, CommonStatusEnum.FREE.getValue(), areaCode);
         }
+        //根据巷到分组，得到每个巷道有多个库位,<巷道编号,库位个数>
+        Map<String, Long> colMap = getColMap(areaCode);
 
         List<PointScore> scoredPoints = availablePoints.stream()
-                .map(point -> clusterPointScore(point, station, itemKeys))
+                .map(point -> clusterPointScore(point, station, itemKeys, colMap))
                 .sorted(Comparator.comparing(PointScore::getScore).reversed())
-                .limit(50)
                 .toList();
 
         if (!scoredPoints.isEmpty()) {
+            log.info("最优【{}】库位评分结果:{}", scoredPoints.get(0).getPoint().getPointCode(), scoredPoints.get(0).getScore());
             return scoredPoints.get(0).getPoint();
         }
 
@@ -221,65 +221,82 @@ public class ScanTrayProcessor {
     /**
      * 库位评分计算
      */
-    private PointScore clusterPointScore(Point point, Point station, List<ItemKey> itemKeys) {
+    private PointScore clusterPointScore(Point point, Point station, List<ItemKey> itemKeys, Map<String, Long> colMap) {
         double totalScore;
 
         // 1. 距离评分 - 考虑从入库口到库位的距离
         double distanceScore = calculateClusterDistanceCost(point, station) * 0.3;// 权重30%
 
         // 2. 通道深度策略评分 - 新增核心策略
-        double channelDepthScore = calculateChannelDepthScore(point) * 0.25; // 权重25%
+        double channelDepthScore = calculateChannelDepthScore(point, colMap) * 0.25; // 权重25%
 
         // 3. 通道类型评分 - 双通道优先
-        double channelScore = calculateChannelScore(point) * 0.15; // 权重15%
+        double channelScore = calculateChannelScore(point) * 0.2; // 权重20%
 
         // 4. 均衡评分 - 避免热点区域
-       // double balanceScore = calculateBalanceScore(point) * 0.1; // 权重10%
+        // double balanceScore = calculateBalanceScore(point) * 0.1; // 权重10%
 
         // 5. 物料聚集潜力评分 - 新增
-       // double clusterPotentialScore = calculateClusterPotentialScore(point, itemKeys) * 0.2; // 权重20%
+        // double clusterPotentialScore = calculateClusterPotentialScore(point, itemKeys) * 0.2; // 权重20%
 
-        totalScore = distanceScore + channelDepthScore + channelScore ;
+        totalScore = distanceScore + channelDepthScore + channelScore;
         log.info("【{}】库位总分:{} - 距离评分: {} - 通道深度策略评分: {} - 通道类型评分: {} - 均衡评分: {} - 物料聚集评分: {}", point.getPointCode(), totalScore, distanceScore, channelDepthScore, channelScore, 0, 0);
         return new PointScore(point, totalScore);
     }
 
     /**
-     * 通道深度策略评分 - 核心优化
+     * 通道深度策略评分 - 核心优化（动态深度）
-     * 双通道：中间优先(04)，向两端扩展
+     * 双通道：中间优先，向两端扩展
-     * 单通道：深度优先(07)，向前扩展
+     * 单通道：深度优先，越靠里分数越高
      */
-    private double calculateChannelDepthScore(Point point) {
+    private double calculateChannelDepthScore(Point point, Map<String, Long> colMap) {
+        // 获取当前巷道的最大深度
+        Long maxDepth = colMap.get(point.getColNum());
         if (point.getIzDoubleLane().equals(1)) {
-            // 双通道策略：中间优先，得分 04 > 03=05 > 02=06 > 01=07
+            return doubleChannelDepthScore(Integer.parseInt(point.getRowNum()), maxDepth);
-            return doubleChannelDepthScore(Integer.parseInt(point.getRowNum()));
         } else {
-            // 单通道策略：深度优先，得分 07 > 06 > 05 > 04 > 03 > 02 > 01
+            return singleChannelDepthScore(Integer.parseInt(point.getRowNum()), maxDepth);
-            return singleChannelDepthScore(Integer.parseInt(point.getRowNum()));
         }
     }
 
     /**
-     * 双通道深度评分
+     * 双通道深度评分（动态深度）
-     * 理想顺序：04 > 03=05 > 02=06 > 01=07
+     * 策略：中间位置最优，向两端递减
      */
-    private double doubleChannelDepthScore(int depth) {
+    private double doubleChannelDepthScore(int depth, long maxDepth) {
-        return switch (depth) {
+        // 计算中间位置
-            case 4 -> 100;  // 最优位置
+        long middle = (maxDepth + 1) / 2;
-            case 3, 5 -> 85;  // 次优位置
+
-            case 2, 6 -> 70;  // 良好位置
+        // 对于偶数深度，中间两个位置分数相同
-            case 1, 7 -> 60;  // 一般位置
+        if (maxDepth % 2 == 0) {
-            default -> 50;
+            if (depth == middle || depth == middle + 1) {
-        };
+                return 100; // 中间最优位置
+            }
+        } else {
+            if (depth == middle) {
+                return 100; // 中间最优位置
+            }
+        }
+
+        // 计算距离中心的偏离程度，偏离越大分数越低
+        double center = (maxDepth + 1) / 2.0;
+        double distanceFromCenter = Math.abs(depth - center);
+
+        // 根据巷道深度调整评分递减幅度，确保评分在合理范围内
+        double maxDistance = Math.max(center - 1, maxDepth - center);
+        if (maxDistance == 0) return 100; // 只有一个位置的情况
+
+        // 使用线性递减，确保边缘位置仍有合理分数
+        return 100 - (distanceFromCenter / maxDistance) * 40;
     }
 
     /**
-     * 单通道深度评分
+     * 单通道深度评分（动态深度）
-     * 理想顺序：07 > 06 > 05 > 04 > 03 > 02 > 01
+     * 策略：深度越大（越靠里）分数越高
      */
-    private double singleChannelDepthScore(int depth) {
+    private double singleChannelDepthScore(int depth, long maxDepth) {
-        // 深度越大分数越高，07得100分，01得14分
+        // 深度越大分数越高，按比例计算
-        return depth * 100.0 / 7;
+        return depth * 100.0 / maxDepth;
     }
 
     /**
@@ -392,8 +409,21 @@ public class ScanTrayProcessor {
     private double calculateClusterDistanceCost(Point point, Point station) {
         // 计算曼哈顿距离
         double distance = Math.abs(point.getPositionX() - station.getPositionX()) + Math.abs(point.getPositionY() - station.getPositionY());
-
+        // 使用更大的标准化参数（根据实际坐标范围）
+        double normalizationFactor = 250000.0; // 或使用动态计算的最大距离值
         // 距离越小分数越高
-        return Math.max(0, 100 - (distance / 100.0));
+        return Math.max(0, 100 - (distance / normalizationFactor) * 100);
     }
+
+    /**
+     * 获取每个巷道的库位个数
+     *
+     * @param areaCode 库区
+     * @return Map<巷道编码, 库位个数>
+     */
+    private Map<String, Long> getColMap(String areaCode) {
+        List<Point> pointList = pointMapper.queryPoints(null, null, areaCode);
+        return pointList.stream().collect(Collectors.groupingBy(Point::getColNum, Collectors.counting()));
+    }
+
 }

cpte-boot-module/cpte-module-wms/src/main/java/org/cpte/modules/receive/service/processor/ReceiveBackProcessor.java

@@ -76,10 +76,10 @@ public class ReceiveBackProcessor {
         parameterValue1.setValue(List.of(task));
 
         SMOMRequest.ParameterValue2 parameterValue2 = new SMOMRequest.ParameterValue2();
-        parameterValue2.setValue(1);
+        parameterValue2.setValue(2);
 
         SMOMRequest.Context context = new SMOMRequest.Context();
-        context.setInvOrgId(1);
+        context.setInvOrgId(2);
         context.setTicket(ticket);
 
         SMOMRequest saiWmsRequest = new SMOMRequest();

cpte-boot-module/cpte-module-wms/src/main/java/org/cpte/modules/shipping/service/processor/PickBackProcessor.java

@@ -84,10 +84,10 @@ public class PickBackProcessor {
         parameterValue1.setValue(List.of(taskReq));
 
         SMOMRequest.ParameterValue2 parameterValue2 = new SMOMRequest.ParameterValue2();
-        parameterValue2.setValue(1);
+        parameterValue2.setValue(2);
 
         SMOMRequest.Context context = new SMOMRequest.Context();
-        context.setInvOrgId(1);
+        context.setInvOrgId(2);
         context.setTicket(ticket);
 
         SMOMRequest saiWmsRequest = new SMOMRequest();

cpte-boot-module/cpte-module-wms/src/main/java/org/cpte/modules/utils/SwmsLoginUtil.java

@@ -24,7 +24,7 @@ public class SwmsLoginUtil {
     private OpenApiMapper openApiMapper;
 
     public String loginJson() {
-        String userName = "LM";
+        String userName = "LIKU";
         String password = "654321";
 
         SMOMRequest.ParameterValue3 parameterValue1 = new SMOMRequest.ParameterValue3();