no message
HUOJIN\92525
parent
2566ff544b
commit
f521e2cb73
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@ -26,10 +26,8 @@ import org.cpte.modules.receive.mapper.AsnMapper;
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import org.springframework.beans.factory.annotation.Autowired;
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import org.springframework.stereotype.Service;
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import java.util.Collections;
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import java.util.Comparator;
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import java.util.List;
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import java.util.Set;
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import java.util.*;
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import java.util.stream.Collectors;
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/**
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* 扫描托盘处理
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@ -204,14 +202,16 @@ public class ScanTrayProcessor {
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//2.获取所有可用库位
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availablePoints = pointMapper.queryPoints(null, CommonStatusEnum.FREE.getValue(), areaCode);
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}
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//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>
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Map<String, Long> colMap = getColMap(areaCode);
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List<PointScore> scoredPoints = availablePoints.stream()
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.map(point -> clusterPointScore(point, station, itemKeys))
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.map(point -> clusterPointScore(point, station, itemKeys, colMap))
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.sorted(Comparator.comparing(PointScore::getScore).reversed())
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.limit(50)
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.toList();
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if (!scoredPoints.isEmpty()) {
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log.info("最优【{}】库位评分结果:{}", scoredPoints.get(0).getPoint().getPointCode(), scoredPoints.get(0).getScore());
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return scoredPoints.get(0).getPoint();
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}
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@ -221,17 +221,17 @@ public class ScanTrayProcessor {
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/**
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* 库位评分计算
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*/
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private PointScore clusterPointScore(Point point, Point station, List<ItemKey> itemKeys) {
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private PointScore clusterPointScore(Point point, Point station, List<ItemKey> itemKeys, Map<String, Long> colMap) {
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double totalScore;
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// 1. 距离评分 - 考虑从入库口到库位的距离
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double distanceScore = calculateClusterDistanceCost(point, station) * 0.3;// 权重30%
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// 2. 通道深度策略评分 - 新增核心策略
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double channelDepthScore = calculateChannelDepthScore(point) * 0.25; // 权重25%
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double channelDepthScore = calculateChannelDepthScore(point, colMap) * 0.25; // 权重25%
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// 3. 通道类型评分 - 双通道优先
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double channelScore = calculateChannelScore(point) * 0.15; // 权重15%
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double channelScore = calculateChannelScore(point) * 0.2; // 权重20%
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// 4. 均衡评分 - 避免热点区域
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// double balanceScore = calculateBalanceScore(point) * 0.1; // 权重10%
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@ -239,47 +239,64 @@ public class ScanTrayProcessor {
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// 5. 物料聚集潜力评分 - 新增
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// double clusterPotentialScore = calculateClusterPotentialScore(point, itemKeys) * 0.2; // 权重20%
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totalScore = distanceScore + channelDepthScore + channelScore ;
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totalScore = distanceScore + channelDepthScore + channelScore;
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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);
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return new PointScore(point, totalScore);
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}
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/**
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* 通道深度策略评分 - 核心优化
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* 双通道：中间优先(04)，向两端扩展
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* 单通道：深度优先(07)，向前扩展
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* 通道深度策略评分 - 核心优化（动态深度）
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* 双通道：中间优先，向两端扩展
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* 单通道：深度优先，越靠里分数越高
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*/
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private double calculateChannelDepthScore(Point point) {
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private double calculateChannelDepthScore(Point point, Map<String, Long> colMap) {
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// 获取当前巷道的最大深度
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Long maxDepth = colMap.get(point.getColNum());
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if (point.getIzDoubleLane().equals(1)) {
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// 双通道策略：中间优先，得分 04 > 03=05 > 02=06 > 01=07
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return doubleChannelDepthScore(Integer.parseInt(point.getRowNum()));
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return doubleChannelDepthScore(Integer.parseInt(point.getRowNum()), maxDepth);
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} else {
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// 单通道策略：深度优先，得分 07 > 06 > 05 > 04 > 03 > 02 > 01
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return singleChannelDepthScore(Integer.parseInt(point.getRowNum()));
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return singleChannelDepthScore(Integer.parseInt(point.getRowNum()), maxDepth);
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}
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}
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/**
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* 双通道深度评分
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* 理想顺序：04 > 03=05 > 02=06 > 01=07
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* 双通道深度评分（动态深度）
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* 策略：中间位置最优，向两端递减
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*/
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private double doubleChannelDepthScore(int depth) {
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return switch (depth) {
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case 4 -> 100; // 最优位置
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case 3, 5 -> 85; // 次优位置
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case 2, 6 -> 70; // 良好位置
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case 1, 7 -> 60; // 一般位置
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default -> 50;
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};
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private double doubleChannelDepthScore(int depth, long maxDepth) {
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// 计算中间位置
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long middle = (maxDepth + 1) / 2;
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// 对于偶数深度，中间两个位置分数相同
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if (maxDepth % 2 == 0) {
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if (depth == middle || depth == middle + 1) {
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return 100; // 中间最优位置
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}
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} else {
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if (depth == middle) {
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return 100; // 中间最优位置
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}
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}
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// 计算距离中心的偏离程度，偏离越大分数越低
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double center = (maxDepth + 1) / 2.0;
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double distanceFromCenter = Math.abs(depth - center);
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// 根据巷道深度调整评分递减幅度，确保评分在合理范围内
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double maxDistance = Math.max(center - 1, maxDepth - center);
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if (maxDistance == 0) return 100; // 只有一个位置的情况
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// 使用线性递减，确保边缘位置仍有合理分数
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return 100 - (distanceFromCenter / maxDistance) * 40;
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}
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/**
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* 单通道深度评分
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* 理想顺序：07 > 06 > 05 > 04 > 03 > 02 > 01
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* 单通道深度评分（动态深度）
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* 策略：深度越大（越靠里）分数越高
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*/
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private double singleChannelDepthScore(int depth) {
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// 深度越大分数越高，07得100分，01得14分
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return depth * 100.0 / 7;
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private double singleChannelDepthScore(int depth, long maxDepth) {
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// 深度越大分数越高，按比例计算
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return depth * 100.0 / maxDepth;
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}
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/**
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@ -392,8 +409,21 @@ public class ScanTrayProcessor {
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private double calculateClusterDistanceCost(Point point, Point station) {
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// 计算曼哈顿距离
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double distance = Math.abs(point.getPositionX() - station.getPositionX()) + Math.abs(point.getPositionY() - station.getPositionY());
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// 使用更大的标准化参数（根据实际坐标范围）
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double normalizationFactor = 250000.0; // 或使用动态计算的最大距离值
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// 距离越小分数越高
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return Math.max(0, 100 - (distance / 100.0));
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return Math.max(0, 100 - (distance / normalizationFactor) * 100);
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}
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/**
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* 获取每个巷道的库位个数
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*
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* @param areaCode 库区
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* @return Map<巷道编码, 库位个数>
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*/
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private Map<String, Long> getColMap(String areaCode) {
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List<Point> pointList = pointMapper.queryPoints(null, null, areaCode);
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return pointList.stream().collect(Collectors.groupingBy(Point::getColNum, Collectors.counting()));
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}
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}
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@ -76,10 +76,10 @@ public class ReceiveBackProcessor {
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parameterValue1.setValue(List.of(task));
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SMOMRequest.ParameterValue2 parameterValue2 = new SMOMRequest.ParameterValue2();
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parameterValue2.setValue(1);
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parameterValue2.setValue(2);
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SMOMRequest.Context context = new SMOMRequest.Context();
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context.setInvOrgId(1);
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context.setInvOrgId(2);
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context.setTicket(ticket);
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SMOMRequest saiWmsRequest = new SMOMRequest();
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@ -84,10 +84,10 @@ public class PickBackProcessor {
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parameterValue1.setValue(List.of(taskReq));
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SMOMRequest.ParameterValue2 parameterValue2 = new SMOMRequest.ParameterValue2();
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parameterValue2.setValue(1);
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parameterValue2.setValue(2);
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SMOMRequest.Context context = new SMOMRequest.Context();
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context.setInvOrgId(1);
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context.setInvOrgId(2);
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context.setTicket(ticket);
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SMOMRequest saiWmsRequest = new SMOMRequest();
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@ -24,7 +24,7 @@ public class SwmsLoginUtil {
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private OpenApiMapper openApiMapper;
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public String loginJson() {
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String userName = "LM";
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String userName = "LIKU";
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String password = "654321";
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SMOMRequest.ParameterValue3 parameterValue1 = new SMOMRequest.ParameterValue3();
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