Skip to content

H
HYH.APSJ
Commit e3a2cdde authored by Tong Li's avatar Tong Li
Browse files
Options

MP

parent 8dc6c378
Expand all Hide whitespace changes
Inline Side-by-side
Showing with 5150 additions and 711 deletions
mp/log/log.txt
View file @ e3a2cdde
This diff is collapsed.
mp/lp/model.lp
View file @ e3a2cdde
This diff is collapsed.
mp/result/optimization_result_1.json
View file @ e3a2cdde
This source diff could not be displayed because it is too large. You can view the blob instead.
src/main/java/com/aps/macroplanner/MacroPlannerOptimizer.java
View file @ e3a2cdde
package com.aps.macroplanner;
import com.aps.common.util.FileHelper;
import com.google.ortools.Loader;
import com.google.ortools.linearsolver.MPSolver;
import com.aps.macroplanner.constraint.ConstraintFactory;
......@@ -89,7 +90,7 @@ public class MacroPlannerOptimizer {
private static final String LP_FILE_PATH = LOG_DIR + "/lp/model.lp";
/** 运行日志文件路径 */
private static final String LOG_FILE_PATH = LOG_DIR + "/log/log.txt";
private static final String LOG_FILE_PATH = LOG_DIR + "/log/";
/** 获取模型容器 (供 ResultWriter 等外部组件使用)。 */
public MacroPlannerModel getModel() { return model; }
......@@ -148,6 +149,11 @@ public class MacroPlannerOptimizer {
rootLogger.addHandler(handler);
}
private void writeLog(String msg)
{
FileHelper.writeFile(msg,LOG_FILE_PATH,"log.txt");
}
// ==================== 模型构建流程 ====================
/**
......@@ -163,32 +169,32 @@ public class MacroPlannerOptimizer {
// 设为 FINE 可输出每个周期的折算详情
configureLogging();
System.out.println("=== 开始构建 MacroPlanner 优化模型 ===\n");
writeLog("=== 开始构建 MacroPlanner 优化模型 ===\n");
// 0. 数据完整性检查 (在构建模型前验证)
DataValidator validator = new DataValidator(data);
if (!validator.validate()) {
System.out.println(" ⚠️ 数据检查发现错误, 求解结果可能不可靠\n");
writeLog(" ⚠️ 数据检查发现错误, 求解结果可能不可靠\n");
} else {
System.out.println(" [OK] 数据检查通过\n");
writeLog(" [OK] 数据检查通过\n");
}
// 1. 决策变量
VariableFactory.createAll(model, data);
System.out.println(" [OK] 决策变量创建完成");
writeLog(" [OK] 决策变量创建完成");
// 2. 约束 + KPI 汇总 (由 ConstraintFactory 统一调度)
ConstraintFactory.buildAll(model, data);
System.out.println(" [OK] 约束与KPI汇总创建完成");
writeLog(" [OK] 约束与KPI汇总创建完成");
// 3. 目标函数 (加权求和)
ObjectiveBuilder.build(model, data);
System.out.println(" [OK] 目标函数创建完成");
writeLog(" [OK] 目标函数创建完成");
// 4. 导出 LP 模型文件
exportLpModel();
System.out.println("\n模型统计: 变量=" + model.getSolver().numVariables()
writeLog("\n模型统计: 变量=" + model.getSolver().numVariables()
+ ", 约束=" + model.getSolver().numConstraints() + "\n");
}
......@@ -211,9 +217,9 @@ public class MacroPlannerOptimizer {
String lpContent = model.getSolver().exportModelAsLpFormat();
Path lpPath = Paths.get(LP_FILE_PATH).toAbsolutePath();
Files.write(lpPath, lpContent.getBytes(StandardCharsets.UTF_8));
System.out.println(" [OK] LP模型文件已导出: " + lpPath);
writeLog(" [OK] LP模型文件已导出: " + lpPath);
} catch (Exception e) {
System.err.println(" [WARN] LP模型导出失败: " + e.getMessage());
writeLog(" [WARN] LP模型导出失败: " + e.getMessage());
}
}
......@@ -255,7 +261,7 @@ public class MacroPlannerOptimizer {
* 每个层级独立求解, 上层最优值作为下层约束, 确保严格优先级顺序。</p>
*/
public void solve() {
System.out.println("=== 开始分层求解 ===\n");
writeLog("=== 开始分层求解 ===\n");
startTimeMs = System.currentTimeMillis();
KPIWeights w = data.getKpiWeights();
......@@ -300,17 +306,20 @@ public class MacroPlannerOptimizer {
if (i < levels.size() - 1 && level.getRelativeGoalSlack() >= 0.0) {
ObjectiveBuilder.addLevelBoundConstraint(model, level, optimalValue);
System.out.printf(" 已添加边界约束: 上层目标 ≤ %.2f%n",
optimalValue * (1.0 + level.getRelativeGoalSlack()));
ObjectiveBuilder.computeUpperBound(optimalValue, level.getRelativeGoalSlack()));
}
System.out.println();
writeLog("-----------------------------------");
}
// 输出最终结果
MPSolver.ResultStatus finalStatus = model.getSolver().solve();
if (finalStatus == MPSolver.ResultStatus.OPTIMAL
|| finalStatus == MPSolver.ResultStatus.FEASIBLE) {
SolutionPrinter printer = new SolutionPrinter(model, data, startTimeMs);
SolutionPrinter printer = new SolutionPrinter(model, data, startTimeMs,LOG_FILE_PATH);
printer.printAll();
// 构建层级最优值列表
List<Double> levelObjValues = new ArrayList<>();
......@@ -323,10 +332,10 @@ public class MacroPlannerOptimizer {
ResultWriter rw = new ResultWriter(model, data, startTimeMs);
boolean jsonPath = rw.saveResultToFile("1");
if (jsonPath) {
System.out.println("\n[OK] 优化结果JSON已导出: " + jsonPath);
writeLog("\n[OK] 优化结果JSON已导出: " + jsonPath);
}
} else {
System.out.println("求解失败! 状态: " + finalStatus);
writeLog("求解失败! 状态: " + finalStatus);
}
}
......
src/main/java/com/aps/macroplanner/constraint/InventorySpecConstraint.java
View file @ e3a2cdde
......@@ -135,7 +135,7 @@ public class InventorySpecConstraint {
} else {
double rhs = spec.getTargetLevel();
MPConstraint c = model.getSolver().makeConstraint(
rhs, rhs, "TargetInv_" + invKey);
rhs, MPSolver.infinity(), "TargetInv_" + invKey);
c.setCoefficient(invVar, 1.0);
MPVariable u = targetUnderVars.get(invKey);
if (u != null) c.setCoefficient(u, 1.0);
......
src/main/java/com/aps/macroplanner/data/MacroPlannerDataConverter.java
View file @ e3a2cdde
......@@ -5,6 +5,7 @@ import com.aps.entity.*;
import com.aps.entity.basic.Material;
import com.aps.entity.basic.MaterialSupply;
import com.aps.mapper.EquipShiftCapacityMapper;
import com.baomidou.mybatisplus.extension.plugins.pagination.Page;
import com.fasterxml.jackson.core.type.TypeReference;
import com.fasterxml.jackson.databind.ObjectMapper;
import com.aps.mapper.EquipinfoMapper;
......@@ -190,6 +191,16 @@ public class MacroPlannerDataConverter {
new LambdaQueryWrapper<ApsDemandOrder>()
.ge(ApsDemandOrder::getDeliverytime, ctx.baseTime)
.lt(ApsDemandOrder::getDeliverytime, horizonEndDateTime));
// ctx.apsDemandOrders = apsDemandOrderMapper.selectList(
//
// new LambdaQueryWrapper<ApsDemandOrder>()
// .ge(ApsDemandOrder::getDeliverytime, ctx.baseTime)
// .eq(ApsDemandOrder::getCode,"XQDD_20260812_6")
// .lt(ApsDemandOrder::getDeliverytime, horizonEndDateTime)
// );
log.info("加载需求订单: {} 条 (时间范围过滤)", ctx.apsDemandOrders.size());
// 2. 收集 materialIds (从 ApsDemandOrder.mmid)
......@@ -215,6 +226,40 @@ public class MacroPlannerDataConverter {
// 4. 工序 (通过 LanuchService 批量查询)
if (!routingIds.isEmpty()) {
List<Integer> routingIds1=routingIds;
// while (routingIds1!=null&&routingIds1.size()>0) {
// List<Routingsupporting> rss = routingsupportingMapper.selectList(
// new LambdaQueryWrapper<Routingsupporting>()
// .in(Routingsupporting::getRoutingHeaderId, routingIds)
// .eq(Routingsupporting::getIsdeleted, 0));
// if (rss != null && rss.size() > 0) {
// Set<String> materialIdrss = rss.stream()
// .map(Routingsupporting::getMaterialId)
// .filter(Objects::nonNull)
// .distinct()
// .collect(Collectors.toSet());
// materialIds.addAll(materialIdrss);
// ctx.routingsupportings.addAll(rss);
//
// List<RoutingHeader> rhs = routingHeaderMapper.selectList(
// new LambdaQueryWrapper<RoutingHeader>()
// .in(RoutingHeader::getMaterialId, materialIdrss));
//
// if (rhs != null && rhs.size() > 0) {
// routingIds1 = rhs.stream()
// .map(RoutingHeader::getId)
// .filter(Objects::nonNull)
// .distinct()
// .collect(Collectors.toList());
// routingIds.addAll(routingIds1);
// ctx.routingHeaders.addAll(rhs);
// } else {
// routingIds1 = null;
// }
// } else {
// routingIds1 = null;
// }
// }
List<Long> routingIdsLong = routingIds.stream()
.map(Long::valueOf)
.collect(Collectors.toList());
......@@ -237,9 +282,12 @@ public class MacroPlannerDataConverter {
// 6. 收集所有 materialId (订单 + 工艺物料消耗 + 工艺路线头表)
ctx.routingsupportings.forEach(rs -> {
if (rs.getMaterialId() != null) materialIds.add(rs.getMaterialId());
});
ctx.routingsupportings.forEach(rs -> {
if (rs.getMaterialId() != null) materialIds.add(rs.getMaterialId());
});
// 7. 物料主数据
......@@ -641,7 +689,7 @@ public class MacroPlannerDataConverter {
// 3.1 为每个 Material 创建 Product
for (Material m : ctx.materialByMaterialId.values()) {
String name = pickName(m.getName(), m.getCode(), m.getId());
Product p = new Product(m.getId(), name);
Product p = new Product(m.getCode(), name);
products.add(p);
ctx.productByMaterialId.put(m.getId(), p);
}
......@@ -892,10 +940,10 @@ public class MacroPlannerDataConverter {
if (inputMaterial == null) {
continue;
}
if (!"MP".equals(inputMaterial.getMaterialTypeName())) {
// 半成品/成品不作为投料, 由各自 Routing 产出
continue;
}
// if (!"MP".equals(inputMaterial.getMaterialTypeName())) {
// // 半成品/成品不作为投料, 由各自 Routing 产出
// continue;
// }
if (rs.getMainQty() == null || rs.getMainQty().compareTo(BigDecimal.ZERO) == 0) {
log.warn("跳过主量为0的BOM项: routingDetailId={}, materialId={}",
......@@ -919,9 +967,11 @@ public class MacroPlannerDataConverter {
// - 有 MATERIAL_PURCHASE → 每供应商一个 Operation, leadTimeDays = purchaseCycle
// - 无 MATERIAL_PURCHASE → 通用供应商 unit, relativeDuration=1, leadTimeDays=0, UnitPeriod 无限
for (Material m : ctx.materialByMaterialId.values()) {
if (!"MP".equals(m.getMaterialTypeName())) {
continue;
}
long headercount= ctx.routingHeaders.stream().filter(t->t.getMaterialId()==m.getId()).count();
if(headercount>0)
{
continue;
}
Product p = ctx.productByMaterialId.get(m.getId());
if (p == null) {
continue;
......@@ -1287,7 +1337,7 @@ public class MacroPlannerDataConverter {
String key = m.getProduct().getId() + "_" + m.getStockingPoint().getId() + "_" + p.getIndex();
if (invSpecKeys.add(key)) {
inventorySpecs.add(new InventorySpec(m.getProduct(), m.getStockingPoint(), p,
0.0, 0.0, LOOSE_MAX, true, true, true));
0.0, 0.0, LOOSE_MAX, false, true, true));
}
}
}
......@@ -1305,7 +1355,7 @@ public class MacroPlannerDataConverter {
for (Operation op : operations) {
if (op.getId().startsWith("OP_PROCURE_")) {
supplySpecs.add(new SupplySpec("Supply-" + op.getId(),
0.0, 0.0, LOOSE_MAX, false, Collections.singletonList(op)));
0.0, 0.0, LOOSE_MAX, true, Collections.singletonList(op)));
}
}
log.info("构建 InventorySpec: {}, SupplySpec: {}", inventorySpecs.size(), supplySpecs.size());
......
src/main/java/com/aps/macroplanner/objective/ObjectiveBuilder.java
View file @ e3a2cdde
......@@ -112,7 +112,21 @@ public class ObjectiveBuilder {
// 设置为最小化目标
objective.setMinimization();
}
/**
* 计算层级边界约束的上界。
*
* <p>松弛比例应允许上层目标值<b>变差</b>（对最小化而言即数值增大）。
* 由于目标值可能为负（负系数 KPI 导致），直接使用
* {@code optimalValue × (1 + slack)} 会在负值时反向收紧约束,
* 因此改用 {@code optimalValue + |optimalValue| × slack}。</p>
*
* @param optimalValue 上层最优目标值
* @param relativeGoalSlack 松弛比例 (>= 0)
* @return 放宽后的上界
*/
public static double computeUpperBound(double optimalValue, double relativeGoalSlack) {
return optimalValue + Math.abs(optimalValue) * relativeGoalSlack;
}
// ==================== 分层优化方法 ====================
/**
......@@ -165,7 +179,7 @@ public class ObjectiveBuilder {
*
* <h3>数学公式</h3>
* <pre>
* Σ (effectiveCoeff × KPI_variable) ≤ optimalValue × (1 + relativeGoalSlack)
* Σ (effectiveCoeff × KPI_variable) ≤ optimalValue + |optimalValue| × relativeGoalSlack
* </pre>
*
* @param model 模型容器
......@@ -178,7 +192,7 @@ public class ObjectiveBuilder {
if (level.getRelativeGoalSlack() < 0.0) return; // 负松弛表示不约束
MPSolver solver = model.getSolver();
double upperBound = optimalValue * (1.0 + level.getRelativeGoalSlack());
double upperBound = computeUpperBound(optimalValue, level.getRelativeGoalSlack());
MPConstraint bound = solver.makeConstraint(
-MPSolver.infinity(), upperBound,
......
src/main/java/com/aps/service/Algorithm/POAOrToolsModel.java 0 → 100644
View file @ e3a2cdde
package com.aps.service.Algorithm;
/**
* 作者：佟礼
* 时间：2026-08-18
*/
public class POAOrToolsModel {
}
Markdown is supported
0% or
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment