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HUOJIN\92525 2026-01-04 17:47:58 +08:00
parent 2566ff544b
commit f521e2cb73
4 changed files with 72 additions and 42 deletions
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98
cpte-boot-module/cpte-module-wms/src/main/java/org/cpte/modules/conveyorLine/service/processor/ScanTrayProcessor.java
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@ -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.Comparator;
import java.util.List;
import java.util.Set;
import java.util.*;
import java.util.stream.Collectors;
/**
* 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();
}
@ -221,17 +221,17 @@ 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%
@ -245,41 +245,58 @@ public class ScanTrayProcessor {
}
/**
* 通道深度策略评分 - 核心优化
* 双通道：中间优先(04)，向两端扩展
* 单通道：深度优先(07)，向前扩展
* 通道深度策略评分 - 核心优化（动态深度）
* 双通道：中间优先，向两端扩展
* 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()));
return doubleChannelDepthScore(Integer.parseInt(point.getRowNum()), maxDepth);
} 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()));
return singleChannelDepthScore(Integer.parseInt(point.getRowNum()), maxDepth);
}
}
/**
* 双通道深度评分
* 理想顺序：04 > 03=05 > 02=06 > 01=07
* 双通道深度评分（动态深度）
* 策略：中间位置最优，向两端递减
*/
private double doubleChannelDepthScore(int depth) {
return switch (depth) {
case 4 -> 100; // 最优位置
case 3, 5 -> 85; // 次优位置
case 2, 6 -> 70; // 良好位置
case 1, 7 -> 60; // 一般位置
default -> 50;
};
private double doubleChannelDepthScore(int depth, long maxDepth) {
// 计算中间位置
long middle = (maxDepth + 1) / 2;
// 对于偶数深度，中间两个位置分数相同
if (maxDepth % 2 == 0) {
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
* 理想顺序：07 > 06 > 05 > 04 > 03 > 02 > 01
* 单通道深度评分（动态深度）
* 策略：深度越大（越靠里）分数越高
*/
private double singleChannelDepthScore(int depth) {
// 深度越大分数越高，07得100分，01得14分
return depth * 100.0 / 7;
private double singleChannelDepthScore(int depth, long maxDepth) {
// 深度越大分数越高，按比例计算
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()));
}
}

4
cpte-boot-module/cpte-module-wms/src/main/java/org/cpte/modules/receive/service/processor/ReceiveBackProcessor.java
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@ -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();

4
cpte-boot-module/cpte-module-wms/src/main/java/org/cpte/modules/shipping/service/processor/PickBackProcessor.java
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@ -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();

2
cpte-boot-module/cpte-module-wms/src/main/java/org/cpte/modules/utils/SwmsLoginUtil.java
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@ -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();