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Commit e3a2cdde authored by Tong Li's avatar Tong Li
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MP

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mp/log/log.txt
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=== MacroPlanner 优化器运行日志 === ===== MACROPLANNER DATA CONVERTER RUNNER START =====
=== 运行时间: 2026-08-17 15:49:44 === SceneId: B288477F1A594DB584C87EEA77880AA3
. ____ _ __ _ _
/\\ / ___'_ __ _ _(_)_ __ __ _ \ \ \ \
( ( )\___ | '_ | '_| | '_ \/ _` | \ \ \ \
\\/ ___)| |_)| | | | | || (_| | ) ) ) )
' |____| .__|_| |_|_| |_\__, | / / / /
=========|_|==============|___/=/_/_/_/
:: Spring Boot :: (v2.7.18)
16:20:33.307 [main] INFO c.a.m.MacroPlannerDataConverterRunner - Starting MacroPlannerDataConverterRunner using Java 1.8.0_201 on DESKTOP-MH00R44 with PID 25004 (F:\product\MES\hyh.apsj\target\classes started by Thinkpad in F:\product\MES\hyh.apsj)
16:20:33.311 [main] INFO c.a.m.MacroPlannerDataConverterRunner - No active profile set, falling back to 1 default profile: "default"
16:20:34.942 [main] INFO o.s.d.r.c.RepositoryConfigurationDelegate - Multiple Spring Data modules found, entering strict repository configuration mode
16:20:34.949 [main] INFO o.s.d.r.c.RepositoryConfigurationDelegate - Bootstrapping Spring Data Redis repositories in DEFAULT mode.
16:20:35.050 [main] INFO o.s.d.r.c.RepositoryConfigurationDelegate - Finished Spring Data repository scanning in 72 ms. Found 0 Redis repository interfaces.
16:20:35.854 [main] INFO o.s.c.s.PostProcessorRegistrationDelegate$BeanPostProcessorChecker - Bean 'spring.datasource.dynamic-com.baomidou.dynamic.datasource.spring.boot.autoconfigure.DynamicDataSourceProperties' of type [com.baomidou.dynamic.datasource.spring.boot.autoconfigure.DynamicDataSourceProperties] is not eligible for getting processed by all BeanPostProcessors (for example: not eligible for auto-proxying)
16:20:35.857 [main] INFO o.s.c.s.PostProcessorRegistrationDelegate$BeanPostProcessorChecker - Bean 'com.baomidou.dynamic.datasource.spring.boot.autoconfigure.DynamicDataSourceAutoConfiguration' of type [com.baomidou.dynamic.datasource.spring.boot.autoconfigure.DynamicDataSourceAutoConfiguration$$EnhancerBySpringCGLIB$$d9e9b6f5] is not eligible for getting processed by all BeanPostProcessors (for example: not eligible for auto-proxying)
16:20:35.879 [main] INFO o.s.c.s.PostProcessorRegistrationDelegate$BeanPostProcessorChecker - Bean 'dsProcessor' of type [com.baomidou.dynamic.datasource.processor.DsHeaderProcessor] is not eligible for getting processed by all BeanPostProcessors (for example: not eligible for auto-proxying)
16:20:37.383 [main] INFO o.s.b.w.e.t.TomcatWebServer - Tomcat initialized with port(s): 8181 (http)
16:20:37.395 [main] INFO o.a.c.http11.Http11NioProtocol - Initializing ProtocolHandler ["http-nio-8181"]
16:20:37.399 [main] INFO o.a.c.core.StandardService - Starting service [Tomcat]
16:20:37.400 [main] INFO o.a.c.core.StandardEngine - Starting Servlet engine: [Apache Tomcat/9.0.83]
16:20:37.680 [main] INFO o.a.c.c.C.[.[localhost].[/] - Initializing Spring embedded WebApplicationContext
16:20:37.680 [main] INFO o.s.b.w.s.c.ServletWebServerApplicationContext - Root WebApplicationContext: initialization completed in 4290 ms
16:20:38.135 [main] INFO c.z.hikari.HikariDataSource - oracle - Starting...
16:20:39.856 [main] INFO c.z.hikari.HikariDataSource - oracle - Start completed.
16:20:39.857 [main] INFO c.b.d.d.DynamicRoutingDataSource - dynamic-datasource - add a datasource named [oracle] success
16:20:39.858 [main] INFO c.b.d.d.DynamicRoutingDataSource - dynamic-datasource initial loaded [1] datasource,primary datasource named [oracle]
16:20:41.489 [main] WARN c.b.m.c.i.DefaultSqlInjector - class com.aps.entity.ApsTimeConfig ,Not found @TableId annotation, Cannot use Mybatis-Plus 'xxById' Method.
_ _ |_ _ _|_. ___ _ | _
| | |\/|_)(_| | |_\ |_)||_|_\
/ |
3.5.6
16:20:44.683 [main] WARN c.b.m.c.i.DefaultSqlInjector - class com.aps.entity.Algorithm.OrderMaterialRequirement ,Not found @TableId annotation, Cannot use Mybatis-Plus 'xxById' Method.
16:20:44.825 [main] INFO c.a.c.g.FileUploadController - 使用已存在的上传目录: F:\product\MES\hyh.apsj\uploads
16:20:46.168 [main] INFO o.s.b.a.w.s.WelcomePageHandlerMapping - Adding welcome page template: index
16:20:46.784 [main] INFO o.a.c.http11.Http11NioProtocol - Starting ProtocolHandler ["http-nio-8181"]
16:20:46.805 [main] INFO o.s.b.w.e.t.TomcatWebServer - Tomcat started on port(s): 8181 (http) with context path ''
16:20:46.828 [main] INFO c.a.m.MacroPlannerDataConverterRunner - Started MacroPlannerDataConverterRunner in 14.371 seconds (JVM running for 15.52)
数据库连接成功！
数据库: Oracle
16:20:46.952 [main] INFO c.a.m.d.MacroPlannerDataConverter - 开始转换场景数据到 macroplanner: sceneId=B288477F1A594DB584C87EEA77880AA3
16:20:47.598 [main] INFO c.a.m.d.MacroPlannerDataConverter - 排产周期: dimension=WEEK, periodCount=6, baseTime=2026-09-28T00:00, horizonEnd=2026-11-09
16:20:47.670 [main] INFO c.a.m.d.MacroPlannerDataConverter - 加载需求订单: 6 条 (时间范围过滤)
16:20:47.843 [main] INFO c.a.m.d.MacroPlannerDataConverter - 加载工艺路线: 9 条
16:20:47.993 [main] INFO c.a.m.d.MacroPlannerDataConverter - 加载工序: 9 条
16:20:48.230 [main] INFO c.a.m.d.MacroPlannerDataConverter - 加载工艺物料消耗: 91 条
16:20:48.460 [main] INFO c.a.m.d.MacroPlannerDataConverter - 加载物料主数据: 47 条
16:20:48.972 [main] INFO c.a.m.d.MacroPlannerDataConverter - 加载库存: 0, 采购: 0, ERP采购订单: 0, 待验: 18, 半成品在途: 39
16:20:49.024 [main] INFO c.a.m.d.MacroPlannerDataConverter - 加载工序设备关联: 9 条
16:20:49.152 [main] INFO c.a.m.d.MacroPlannerDataConverter - 加载设备资源: 7, 设备信息: 7
16:20:49.522 [main] INFO c.a.m.d.MacroPlannerDataConverter - 加载设备产能日历(EquipShiftCapacity): 294 条 (时间范围过滤)
16:20:49.534 [main] INFO c.a.m.d.MacroPlannerDataConverter - 构建 Material 业务对象: 47 个
16:20:49.534 [main] INFO c.a.m.d.MacroPlannerDataConverter - 排产周期: dimension=WEEK, periodCount=6, horizonEnd=2026-11-09
16:20:49.581 [main] INFO c.a.m.d.MacroPlannerDataConverter - 设备日产能(EquipShiftCapacity): 7 台设备, 1 台有节假日, 默认=16.0h
16:20:49.584 [main] INFO c.a.m.d.MacroPlannerDataConverter - 构建 Product: 47, StockingPoint: 1
16:20:49.587 [main] INFO c.a.macroplanner.data.Routing - [路由展开] 开始: R_644735 '104车间-5号线灭菌水50支10ml' → 产品=A24001 最终库存点=SP_472 工序数=1
16:20:49.588 [main] INFO c.a.macroplanner.data.Routing - [路由展开] 单步路由: 'OP_644735_660272' 产出 → A24001@SP_472 (产出数: 0→1)
16:20:49.589 [main] INFO c.a.macroplanner.data.Routing - [路由展开] 开始: R_643441 '10%葡萄糖注射液' → 产品=D61001U 最终库存点=SP_472 工序数=1
16:20:49.589 [main] INFO c.a.macroplanner.data.Routing - [路由展开] 单步路由: 'OP_643441_659747' 产出 → D61001U@SP_472 (产出数: 0→1)
16:20:49.589 [main] INFO c.a.macroplanner.data.Routing - [路由展开] 开始: R_643736 '甘露醇注射液' → 产品=D53014 最终库存点=SP_472 工序数=1
16:20:49.589 [main] INFO c.a.macroplanner.data.Routing - [路由展开] 单步路由: 'OP_643736_659348' 产出 → D53014@SP_472 (产出数: 0→1)
16:20:49.589 [main] INFO c.a.macroplanner.data.Routing - [路由展开] 开始: R_643663 '0.9%氯化钠注射液' → 产品=D89004U 最终库存点=SP_472 工序数=1
16:20:49.589 [main] INFO c.a.macroplanner.data.Routing - [路由展开] 单步路由: 'OP_643663_659422' 产出 → D89004U@SP_472 (产出数: 0→1)
16:20:49.589 [main] INFO c.a.macroplanner.data.Routing - [路由展开] 开始: R_643686 '乳酸左氧氟沙星氯化钠注射液' → 产品=D66546U 最终库存点=SP_472 工序数=1
16:20:49.589 [main] INFO c.a.macroplanner.data.Routing - [路由展开] 单步路由: 'OP_643686_659399' 产出 → D66546U@SP_472 (产出数: 0→1)
16:20:49.589 [main] INFO c.a.macroplanner.data.Routing - [路由展开] 开始: R_643717 '10%葡萄糖注射液' → 产品=D61001U 最终库存点=SP_472 工序数=1
16:20:49.589 [main] INFO c.a.macroplanner.data.Routing - [路由展开] 单步路由: 'OP_643717_659369' 产出 → D61001U@SP_472 (产出数: 0→1)
16:20:49.589 [main] INFO c.a.macroplanner.data.Routing - [路由展开] 开始: R_644161 '甘露醇注射液' → 产品=D53014 最终库存点=SP_472 工序数=1
16:20:49.589 [main] INFO c.a.macroplanner.data.Routing - [路由展开] 单步路由: 'OP_644161_656815' 产出 → D53014@SP_472 (产出数: 0→1)
16:20:49.590 [main] INFO c.a.m.d.MacroPlannerDataConverter - 构建 Routing: 7, Operation: 7
16:20:49.591 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 c7f9de08-358b-2247-8e45-07bdeecbe626 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.591 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 cfd0dd08-982b-ef49-8b11-f42c13f76058 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.591 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 cfd0dd08-98e4-de4b-8466-a0063eb17440 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.591 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 ccd0dd08-b389-7c43-881b-3617e270e0c1 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.591 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 cfd0dd08-212d-9041-8008-534b9a5c5116 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.591 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 cfd0dd08-5a2b-fb4f-8e58-35c78327c069 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.591 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 cfd0dd08-abc0-564d-8fcf-07440af92534 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.591 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 cfd0dd08-9c2c-ba4a-8483-12dd4b747d64 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.591 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 ccd0dd08-ab85-a84f-824b-68a9ad8078e9 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.591 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 ced0dd08-3c6b-db40-86b7-09cc87bc86cf 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.591 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 cfd0dd08-8120-3f4e-8c4e-1f25bf980000 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.591 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 cfd0dd08-d0b9-8141-8e26-811f9a47d167 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.591 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 cdd0dd08-5752-a14c-8b95-43b8c1879d7b 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.592 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 cfd0dd08-8fe3-774e-8aa3-11fcd7c566b3 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.592 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 cdd0dd08-4aa1-4141-890f-b65b39cee506 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.592 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 ced0dd08-1ff4-5541-8688-b667e88fdfb6 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.592 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 cdd0dd08-5d98-794b-82aa-fd0fa7a5ae55 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.592 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 cdd0dd08-a27e-dc47-8976-ec9ae348c2b1 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.592 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 d0d0dd08-275c-e24b-8267-3db6b56ec68f 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.592 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 cfd0dd08-b70d-134f-85c6-40cb6a8c07fd 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.592 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 cdd0dd08-e0e9-254b-8908-ed292fc0b2b0 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.593 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 cfd0dd08-092f-d44e-8504-f70fc6b8d214 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.593 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 cfd0dd08-e02c-3b4d-8710-a11570027450 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.593 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 cfd0dd08-36e2-d04b-8b0b-2ef4550eb809 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.593 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 cdd0dd08-d398-ec4c-8e50-e6365a3ea831 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.593 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 ccd0dd08-278f-9e47-862a-061ccbadad7d 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.593 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 d0d0dd08-7a56-5b47-8046-ddebc3c82c32 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.593 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 cfd0dd08-5c2c-6f47-88fa-9c12f6423db9 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.593 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 cdd0dd08-2666-4f4a-8ef3-f4a2c3fce8dc 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.594 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 cfd0dd08-0c15-1b43-8bff-c81b34b6e5fe 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.594 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 cdd0dd08-6c88-db4a-85ff-8749f8dce853 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.594 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 cdd0dd08-73da-0d47-8f89-9b1e37b7dfbd 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.594 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 cfd0dd08-3922-1248-859b-6108cf0b47f0 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.594 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 ccf9de08-be3d-7545-8eab-2dc71fee1294 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.594 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 ced0dd08-35f5-a444-882a-e7ae29bb27cc 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.594 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 cfd0dd08-8608-ba49-8e97-db7c85c1b84d 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.594 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 cdd0dd08-a696-1544-89ca-8e41292db881 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.594 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 cdd0dd08-9b80-714b-808c-9a90a588a8c7 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.595 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 ced0dd08-a33d-d64b-88d3-7df77ee6c023 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.595 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 ccd0dd08-7b84-5a42-8650-79e5f044251f 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.595 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 cfd0dd08-0121-4b44-85f6-777dee3d1eba 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.595 [main] INFO c.a.m.d.MacroPlannerDataConverter - 为 MP 原材料 cfd0dd08-5b6a-e446-8dc2-4fa39855a2cb 创建通用采购 Operation (无供应商, 无限产能)
16:20:49.595 [main] INFO c.a.m.d.MacroPlannerDataConverter - 构建 OperationInput: 75
16:20:49.596 [main] INFO c.a.m.d.MacroPlannerDataConverter - 构建 InitialInventory: 0, InTransitSupply: 57
16:20:49.598 [main] INFO c.a.m.d.MacroPlannerDataConverter - 构建 Period: 6 (dimension=WEEK, horizonEnd=2026-11-09), UnitPeriod: 48
16:20:49.598 [main] INFO c.a.m.d.MacroPlannerDataConverter - 构建 SalesDemand: 16
16:20:49.600 [main] INFO c.a.m.d.MacroPlannerDataConverter - 构建 InventorySpec: 282, SupplySpec: 49
16:20:49.600 [main] INFO c.a.m.d.MacroPlannerDataConverter - 转换完成: products=47, stockingPoints=1, operations=49, routings=7, operationInputs=75, initialInventories=0, inTransitSupplies=57, salesDemands=16
Data converted:
Products: 47
StockingPoints: 1
Operations: 49
Routings: 7
OperationInputs: 75
InitialInventories: 0
InTransitSupplies: 57
SalesDemands: 16
Periods: 6
UnitPeriods: 48
16:20:49.603 [main] INFO c.a.m.data.DataValidator - ✅ 数据检查通过: 无错误, 无警告
DataValidator: valid=true
=== 开始构建 MacroPlanner 优化模型 === === 开始构建 MacroPlanner 优化模型 ===
[警告] ========== 数据检查: 4 个警告 ==========
[警告] ⚠️ 工序 OP_R1 leadTimeDays=1 天, 但第一个周期前无对应生产周期, 第1周期该产品无到货
[警告] ⚠️ 工序 OP_R1_Alt leadTimeDays=2 天, 但第一个周期前无对应生产周期, 第1周期该产品无到货
[警告] ⚠️ 工序 OP_R2 leadTimeDays=1 天, 但第一个周期前无对应生产周期, 第1周期该产品无到货
[警告] ⚠️ 工序 OP_R2_Alt leadTimeDays=3 天, 但第一个周期前无对应生产周期, 第1周期该产品无到货
[信息] ✅ 数据检查通过: 无错误, 4 个警告
[OK] 数据检查通过 [OK] 数据检查通过
[信息] ✅ 数据检查通过: 无错误, 无警告
[OK] 决策变量创建完成 [OK] 决策变量创建完成
[信息] ========== 开始构建约束 ========== [信息] ========== 开始构建约束 ==========
[信息] [1. 物料平衡] 确保每个 PISPIP 流入 = 流出 | +15约束 [信息] [1. 物料平衡] 确保每个 PISPIP 流入 = 流出 | +282约束
[信息] [2. BOM依赖需求] OperationDemandQty = PTQty × BOM因子 | +27约束 [信息] [2. BOM依赖需求] OperationDemandQty = PTQty × BOM因子 | +732约束
[信息] [3. 需求满足量汇总] DemandFulfillment = SalesDemandQty + OperationDemandQty | +15约束 [信息] [3. 需求满足量汇总] DemandFulfillment = SalesDemandQty + OperationDemandQty | +282约束
[信息] [4. 需求缺口联动] SalesDemandQty + DemandSlack >= DemandQuantity | +6约束 [信息] [4. 需求缺口联动] SalesDemandQty + DemandSlack >= DemandQuantity | +14约束
[警告] [4.5 工序产量一致] Routing 内相邻工序 PTQty 相等, 防止 WIP 堆积 → 未创建任何约束或变量! (可能数据为空) [警告] [4.5 工序产量一致] Routing 内相邻工序 PTQty 相等, 防止 WIP 堆积 → 未创建任何约束或变量! (可能数据为空)
[信息] [库存规格] 构建完成: 0 个使用安全库存天数, 45 个使用绝对数量 [信息] [库存规格] 构建完成: 0 个使用安全库存天数, 846 个使用绝对数量
[信息] [5. 库存规格] InvQty + Slack ≥ Min/Max/Target (支持天数模式) | +45约束 [信息] [5. 库存规格] InvQty + Slack ≥ Min/Max/Target (支持天数模式) | +846约束
[信息] [6. 产能约束] Σ(PTQty×coeff) ∈ [MinCapacity, MaxCapacity] | +9约束 [信息] [6. 产能约束] Σ(PTQty×coeff) ∈ [MinCapacity, MaxCapacity] | +42约束
[信息] [7. 供应规格] ΣPTQty + Slack ≥ Target/Min/Max | +14约束 [信息] [7. 供应规格] ΣPTQty + Slack ≥ Target/Min/Max | +98约束
[信息] [8. 批次大小] PTQty×QTPFactor + Slack ∈ [LotSize] | +24约束 [警告] [8. 批次大小] PTQty×QTPFactor + Slack ∈ [LotSize] → 未创建任何约束或变量! (可能数据为空)
[信息] [9. KPI汇总] TotalKPI = Σ 松弛变量 (12个KPI) | +10约束 | +12变量 [信息] [9. KPI汇总] TotalKPI = Σ 松弛变量 (12个KPI) | +10约束 | +12变量
[信息] ========== 约束构建完成: 总计 165 约束, 218 变量 ========== [信息] ========== 约束构建完成: 总计 2306 约束, 2928 变量 ==========
[OK] 约束与KPI汇总创建完成 [OK] 约束与KPI汇总创建完成
[OK] 目标函数创建完成 [OK] 目标函数创建完成
[OK] LP模型文件已导出: F:\product\MES\hyh.apsj\mp\lp\model.lp [OK] LP模型文件已导出: F:\product\MES\hyh.apsj\mp\lp\model.lp
模型统计: 变量=218, 约束=165 模型统计: 变量=2928, 约束=2306
=== 开始分层求解 === === 开始分层求解 ===
--- 第 1/4 层: 需求满足 (松弛=0%) --- --- 第 1/4 层: 需求满足 (松弛=0%) ---
SCIP Status : OPTIMAL presolving:
Solving Time (sec) : 0.01 (round 1, fast) 1616 del vars, 1668 del conss, 0 add conss, 631 chg bounds, 0 chg sides, 0 chg coeffs, 0 upgd conss, 0 impls, 0 clqs, 0 implints
Primal Bound : +1.950000e+04 presolving (2 rounds: 2 fast, 0 medium, 0 exhaustive):
需求缺口: 195.00 (系数=100.0, 惩罚=19500.00) 2193 deleted vars, 1694 deleted constraints, 0 added constraints, 715 tightened bounds, 0 added holes, 0 changed sides, 0 changed coefficients
已添加边界约束: 上层目标 ≤ 19500.00 0 implications, 0 cliques, 0 implied integral variables (0 bin, 0 int, 0 cont)
presolving detected infeasibility
Presolving Time: 0.00
SCIP Status : problem is solved [infeasible]
Solving Time (sec) : 0.00
Solving Nodes : 0
Primal Bound : +1.00000000000000e+20 (0 solutions)
Dual Bound : +1.00000000000000e+20
Gap : 0.00 %
SCIP Status : INFEASIBLE
Solving Time (sec) : 0.02
Primal Bound : +0.000000e+00
需求缺口: 0.00 (系数=100.0, 惩罚=0.00)
已添加边界约束: 上层目标 ≤ 0.00
--- 第 2/4 层: 产能约束 (松弛=0%) --- --- 第 2/4 层: 产能约束 (松弛=0%) ---
SCIP Status : OPTIMAL presolving:
Solving Time (sec) : 0.01 presolving (1 rounds: 1 fast, 0 medium, 0 exhaustive):
1616 deleted vars, 1668 deleted constraints, 0 added constraints, 631 tightened bounds, 0 added holes, 0 changed sides, 0 changed coefficients
0 implications, 0 cliques, 0 implied integral variables (0 bin, 0 int, 0 cont)
presolving detected infeasibility
Presolving Time: 0.00
SCIP Status : problem is solved [infeasible]
Solving Time (sec) : 0.00
Solving Nodes : 0
Primal Bound : +1.00000000000000e+20 (0 solutions)
Dual Bound : +1.00000000000000e+20
Gap : 0.00 %
SCIP Status : INFEASIBLE
Solving Time (sec) : 0.02
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1787127650.835447 31160 linear_solver.cc:1891] No solution exists. MPSolverInterface::result_status_ = MPSOLVER_INFEASIBLE
E0000 00:00:1787127650.835997 31160 linear_solver.cc:1891] No solution exists. MPSolverInterface::result_status_ = MPSOLVER_INFEASIBLE
E0000 00:00:1787127650.854022 31160 linear_solver.cc:1891] No solution exists. MPSolverInterface::result_status_ = MPSOLVER_INFEASIBLE
E0000 00:00:1787127650.854375 31160 linear_solver.cc:1891] No solution exists. MPSolverInterface::result_status_ = MPSOLVER_INFEASIBLE
Primal Bound : +0.000000e+00 Primal Bound : +0.000000e+00
产能超载: 0.00 (系数=20.0, 惩罚=0.00) 产能超载: 0.00 (系数=3.0, 惩罚=0.00)
已添加边界约束: 上层目标 ≤ 0.00 已添加边界约束: 上层目标 ≤ 0.00
--- 第 3/4 层: 业务KPI (松弛=5%) --- --- 第 3/4 层: 业务KPI (松弛=5%) ---
SCIP Status : OPTIMAL presolving:
presolving (1 rounds: 1 fast, 0 medium, 0 exhaustive):
1616 deleted vars, 1668 deleted constraints, 0 added constraints, 631 tightened bounds, 0 added holes, 0 changed sides, 0 changed coefficients
0 implications, 0 cliques, 0 implied integral variables (0 bin, 0 int, 0 cont)
presolving detected infeasibility
Presolving Time: 0.00
SCIP Status : problem is solved [infeasible]
Solving Time (sec) : 0.00
Solving Nodes : 0
Primal Bound : +1.00000000000000e+20 (0 solutions)
Dual Bound : +1.00000000000000e+20
Gap : 0.00 %
SCIP Status : INFEASIBLE
Solving Time (sec) : 0.01 Solving Time (sec) : 0.01
Primal Bound : +6.405000e+03 Primal Bound : +0.000000e+00
批次偏差: 466.67 (系数=10.0, 惩罚=4666.67) 批次偏差: 0.00 (系数=10.0, 惩罚=0.00)
目标库存偏差: 195.00 (系数=8.0, 惩罚=1560.00) 目标库存偏差: 0.00 (系数=8.0, 惩罚=0.00)
供应目标偏差: 81.67 (系数=8.0, 惩罚=653.33) 供应目标偏差: 0.00 (系数=8.0, 惩罚=0.00)
销售优先级: 475.00 (系数=-1.0, 惩罚=-475.00) 销售优先级: 0.00 (系数=-1.0, 惩罚=-0.00)
已添加边界约束: 上层目标 ≤ 6725.25 已添加边界约束: 上层目标 ≤ 0.00
--- 第 4/4 层: 软约束 (松弛=10%) --- --- 第 4/4 层: 软约束 (松弛=10%) ---
SCIP Status : OPTIMAL presolving:
Solving Time (sec) : 0.01 E0000 00:00:1787127650.869440 31160 linear_solver.cc:1891] No solution exists. MPSolverInterface::result_status_ = MPSOLVER_INFEASIBLE
Primal Bound : +1.900000e+02 E0000 00:00:1787127650.869813 31160 linear_solver.cc:1891] No solution exists. MPSolverInterface::result_status_ = MPSOLVER_INFEASIBLE
E0000 00:00:1787127650.869967 31160 linear_solver.cc:1891] No solution exists. MPSolverInterface::result_status_ = MPSOLVER_INFEASIBLE
E0000 00:00:1787127650.870092 31160 linear_solver.cc:1891] No solution exists. MPSolverInterface::result_status_ = MPSOLVER_INFEASIBLE
E0000 00:00:1787127650.870214 31160 linear_solver.cc:1891] No solution exists. MPSolverInterface::result_status_ = MPSOLVER_INFEASIBLE
presolving (1 rounds: 1 fast, 0 medium, 0 exhaustive):
1616 deleted vars, 1667 deleted constraints, 0 added constraints, 631 tightened bounds, 0 added holes, 0 changed sides, 0 changed coefficients
0 implications, 0 cliques, 0 implied integral variables (0 bin, 0 int, 0 cont)
presolving detected infeasibility
Presolving Time: 0.00
SCIP Status : problem is solved [infeasible]
Solving Time (sec) : 0.00
Solving Nodes : 0
Primal Bound : +1.00000000000000e+20 (0 solutions)
Dual Bound : +1.00000000000000e+20
Gap : 0.00 %
SCIP Status : INFEASIBLE
Solving Time (sec) : 0.02
Primal Bound : +0.000000e+00
超库存: 0.00 (系数=5.0, 惩罚=0.00) 超库存: 0.00 (系数=5.0, 惩罚=0.00)
欠库存: 38.00 (系数=5.0, 惩罚=190.00) 欠库存: 0.00 (系数=5.0, 惩罚=0.00)
最小供应不足: 0.00 (系数=5.0, 惩罚=0.00) 最小供应不足: 0.00 (系数=5.0, 惩罚=0.00)
最大供应超出: 0.00 (系数=5.0, 惩罚=0.00) 最大供应超出: 0.00 (系数=5.0, 惩罚=0.00)
📋 BOM关系验证: 求解失败! 状态: INFEASIBLE
P1 → 消耗: [S1@WH_Semi×2, R1@WH_RM×3], 被消耗于: [] ===== MACROPLANNER DATA CONVERTER RUNNER END =====
P2 → 消耗: [S1@WH_Semi×1], 被消耗于: [] E0000 00:00:1787127650.891040 31160 linear_solver.cc:1891] No solution exists. MPSolverInterface::result_status_ = MPSOLVER_INFEASIBLE
S1 → 消耗: [R2@WH_RM×2], 被消耗于: [P1@WH_FG×2, P2@WH_FG×1] E0000 00:00:1787127650.891428 31160 linear_solver.cc:1891] No solution exists. MPSolverInterface::result_status_ = MPSOLVER_INFEASIBLE
R1 → 消耗: [], 被消耗于: [P1@WH_FG×3] E0000 00:00:1787127650.891629 31160 linear_solver.cc:1891] No solution exists. MPSolverInterface::result_status_ = MPSOLVER_INFEASIBLE
R2 → 消耗: [], 被消耗于: [S1@WH_Semi×2] E0000 00:00:1787127650.891779 31160 linear_solver.cc:1891] No solution exists. MPSolverInterface::result_status_ = MPSOLVER_INFEASIBLE
E0000 00:00:1787127650.891958 31160 linear_solver.cc:1891] No solution exists. MPSolverInterface::result_status_ = MPSOLVER_INFEASIBLE
========== 网状BOM + MRP 排产求解 ========== [信息] Pausing ProtocolHandler ["http-nio-8181"]
成品(根节点) 2 种：P1 P2 [警告] Failed to unlock acceptor for [http-nio-8181] because the local address was not available
生产品 5 种：P1 P2 S1 R1 R2 [信息] Stopping service [Tomcat]
周期 3 天 [严重] Socket accept failed
[信息] Stopping ProtocolHandler ["http-nio-8181"]
[信息] Destroying ProtocolHandler ["http-nio-8181"]
═══════════════════ 第 1 天 ═══════════════════ 16:20:53.719 [main] INFO c.b.d.d.DynamicRoutingDataSource - dynamic-datasource start closing ....
▶ 产线视图（按产线分组） 16:20:53.719 [main] INFO c.z.hikari.HikariDataSource - oracle - Shutdown initiated...
【L1】产能10h 16:20:54.287 [main] INFO c.z.hikari.HikariDataSource - oracle - Shutdown completed.
Make-P1(P1): 40件 (耗时4.0h) 16:20:54.287 [main] INFO c.b.d.d.DynamicRoutingDataSource - dynamic-datasource all closed success,bye
利用率: 4/10 h (40%)
【L2】产能10h
Make-S1(S1): 50件 (耗时1.7h)
利用率: 2/10 h (17%)
【L3】产能10h
Make-P2(P2): 20件 (耗时3.3h)
利用率: 3/10 h (33%)
【SuA】产能无限 (供应商)
Procure-R1(R1): 200件 (耗时24.0h)
【SuB】产能无限 (供应商)
Procure-R1-Alt(R1): 150件 (耗时36.0h)
【Su1】产能无限 (供应商)
Procure-R2(R2): 446件 (耗时71.4h)
【Su2】产能无限 (供应商)
Procure-R2-Alt(R2): 150件 (耗时45.0h)
▶ 产品视图（汇总各产线产量）
P1@WH_FG: 期初库存20件 → 期末库存0件 [目标20/最小5/最大150] | 到货共40件 [L1(到货40件)] 生产中40件 ⚠需求缺口195件 | 销售255/450件 ⚠未满足195件 [库存耗尽(可用60件, 需求450件)]
P2@WH_FG: 期初库存10件 → 期末库存0件 [目标15/最小3/最大120] | 到货共20件 [L3(到货20件)] 生产中20件 | 销售30/30件
S1@WH_Semi: 期初库存50件 → 期末库存0件 [目标30/最小10/最大200] | 到货共50件 [L2(到货50件)] 生产中50件 | 销售0/0件
R1@WH_RM: 期初库存200件 → 期末库存80件 [目标80/最小50/最大500] | 无到货 | 销售0/0件
R2@WH_RM: 期初库存100件 → 期末库存0件 [目标40/最小20/最大400] | 无到货 | 销售0/0件
▶ 物料需求展开（按BOM逐级展开）
Make-P1(P1)生产40件 →
─── 物料需求汇总 ───
S1(生产): 期初库存50件, 今日生产50件, 今日需求80件, 期末库存0件
└ S1需求80件(由P1×2系数)
─── 物料需求汇总 ───
R1(采购): 期初库存200件, 今日生产350件, 今日需求120件, 期末库存80件
└ R1需求120件(由P1×3系数)
Make-P2(P2)生产20件 →
─── 物料需求汇总 ───
S1(生产): 期初库存50件, 今日生产50件, 今日需求20件, 期末库存0件
└ S1需求20件(由P2×1系数)
Make-S1(S1)生产50件 →
─── 物料需求汇总 ───
R2(采购): 期初库存100件, 今日生产596件, 今日需求100件, 期末库存0件
└ R2需求100件(由S1×2系数)
Procure-R1(R1)生产200件 →
Procure-R1-Alt(R1)生产150件 →
Procure-R2(R2)生产446件 →
Procure-R2-Alt(R2)生产150件 →
▶ 期末库存 P1@WH_FG=0 P2@WH_FG=0 S1@WH_Semi=0 R1@WH_RM=80 R2@WH_RM=0
═══════════════════ 第 2 天 ═══════════════════
▶ 产线视图（按产线分组）
【L1】产能10h
Make-P1(P1): 67件 (耗时6.7h)
利用率: 7/10 h (67%)
Make-P2(P2): 27件 (耗时3.3h)
利用率: 3/10 h (33%)
【L2】产能10h
Make-S1(S1): 203件 (耗时6.8h)
利用率: 7/10 h (68%)
【L3】产能10h
Make-P2(P2): 16件 (耗时2.7h)
利用率: 3/10 h (27%)
【SuA】产能无限 (供应商)
（休息）
【SuB】产能无限 (供应商)
Procure-R1-Alt(R1): 150件 (耗时36.0h)
【Su1】产能无限 (供应商)
Procure-R2(R2): 266件 (耗时42.6h)
【Su2】产能无限 (供应商)
Procure-R2-Alt(R2): 150件 (耗时45.0h)
▶ 产品视图（汇总各产线产量）
P1@WH_FG: 上期库存0件 → 期末库存7件 [目标20/最小5/最大150] | 到货共66.7件 [L1(到货67件)] 生产中66.7件 | 销售60/60件
P2@WH_FG: 上期库存0件 → 期末库存3件 [目标15/最小3/最大120] | 到货共43件 [L1(到货27件), L3(到货16件)] 生产中43件 | 销售40/40件
S1@WH_Semi: 上期库存0件 → 期末库存27件 [目标30/最小10/最大200] | 到货共203.1件 [L2(到货203件)] 生产中203.1件 | 销售0/0件
R1@WH_RM: 上期库存80件 → 期末库存80件 [目标80/最小50/最大500] | 到货共200件 [SuA(到货200件)] 生产中150件 | 销售0/0件
R2@WH_RM: 上期库存0件 → 期末库存40件 [目标40/最小20/最大400] | 到货共446.2件 [Su1(到货446件)] 生产中416.3件 | 销售0/0件
▶ 物料需求展开（按BOM逐级展开）
Make-P1(P1)生产67件 →
─── 物料需求汇总 ───
S1(生产): 期初库存0件, 今日生产203件, 今日需求133件, 期末库存27件
└ S1需求133件(由P1×2系数)
─── 物料需求汇总 ───
R1(采购): 期初库存80件, 今日生产150件, 今日需求200件, 期末库存80件
└ R1需求200件(由P1×3系数)
Make-P2(P2)生产43件 →
─── 物料需求汇总 ───
S1(生产): 期初库存0件, 今日生产203件, 今日需求43件, 期末库存27件
└ S1需求43件(由P2×1系数)
Make-S1(S1)生产203件 →
─── 物料需求汇总 ───
R2(采购): 期初库存0件, 今日生产416件, 今日需求406件, 期末库存40件
└ R2需求406件(由S1×2系数)
Procure-R1-Alt(R1)生产150件 →
Procure-R2(R2)生产266件 →
Procure-R2-Alt(R2)生产150件 →
▶ 期末库存 P1@WH_FG=7 P2@WH_FG=3 S1@WH_Semi=27 R1@WH_RM=80 R2@WH_RM=40
═══════════════════ 第 3 天 ═══════════════════
▶ 产线视图（按产线分组）
【L1】产能10h
Make-P1(P1): 50件 (耗时5.0h)
利用率: 5/10 h (50%)
【L2】产能10h
Make-S1(S1): 143件 (耗时4.8h)
利用率: 5/10 h (48%)
【L3】产能10h
Make-P2(P2): 60件 (耗时10.0h)
利用率: 10/10 h (100%)
【SuA】产能无限 (供应商)
Procure-R1(R1): 200件 (耗时24.0h)
【SuB】产能无限 (供应商)
Procure-R1-Alt(R1): 150件 (耗时36.0h)
【Su1】产能无限 (供应商)
Procure-R2(R2): 200件 (耗时32.0h)
【Su2】产能无限 (供应商)
Procure-R2-Alt(R2): 150件 (耗时45.0h)
▶ 产品视图（汇总各产线产量）
P1@WH_FG: 上期库存7件 → 期末库存17件 [目标20/最小5/最大150] | 到货共50件 [L1(到货50件)] 生产中50件 | 销售40/40件
P2@WH_FG: 上期库存3件 → 期末库存13件 [目标15/最小3/最大120] | 到货共59.9件 [L3(到货60件)] 生产中59.9件 | 销售50/50件
S1@WH_Semi: 上期库存27件 → 期末库存10件 [目标30/最小10/最大200] | 到货共143.1件 [L2(到货143件)] 生产中143.1件 | 销售0/0件
R1@WH_RM: 上期库存80件 → 期末库存80件 [目标80/最小50/最大500] | 到货共150件 [SuB(到货150件)] 生产中350件 | 销售0/0件
R2@WH_RM: 上期库存40件 → 期末库存20件 [目标40/最小20/最大400] | 到货共266.3件 [Su1(到货266件)] 生产中350件 | 销售0/0件
▶ 物料需求展开（按BOM逐级展开）
Make-P1(P1)生产50件 →
─── 物料需求汇总 ───
S1(生产): 期初库存27件, 今日生产143件, 今日需求100件, 期末库存10件
└ S1需求100件(由P1×2系数)
─── 物料需求汇总 ───
R1(采购): 期初库存80件, 今日生产350件, 今日需求150件, 期末库存80件
└ R1需求150件(由P1×3系数)
Make-P2(P2)生产60件 →
─── 物料需求汇总 ───
S1(生产): 期初库存27件, 今日生产143件, 今日需求60件, 期末库存10件
└ S1需求60件(由P2×1系数)
Make-S1(S1)生产143件 →
─── 物料需求汇总 ───
R2(采购): 期初库存40件, 今日生产350件, 今日需求286件, 期末库存20件
└ R2需求286件(由S1×2系数)
Procure-R1(R1)生产200件 →
Procure-R1-Alt(R1)生产150件 →
Procure-R2(R2)生产200件 →
Procure-R2-Alt(R2)生产150件 →
▶ 期末库存 P1@WH_FG=17 P2@WH_FG=13 S1@WH_Semi=10 R1@WH_RM=80 R2@WH_RM=20
═══════════════════ KPI 汇总 ═══════════════════
目标函数值 (最小总惩罚): 190.00
需求缺口惩罚: 19500.00 (权重100 × 195.00)
批次偏差惩罚: 5124.27 (权重10 × 512.43)
超库存惩罚: 0.00 (权重5 × 0.00)
欠库存惩罚: 190.00 (权重5 × 38.00)
目标库存偏差: 1432.35 (权重8 × 179.04)
产能超载惩罚: 0.00 (权重20 × 0.00)
供应目标偏差: 643.62 (权重8 × 80.45)
最小供应不足: 0.00 (权重5 × 0.00)
最大供应超出: 0.00 (权重5 × 0.00)
销售优先级(负): 475.00 (权重1 × 475.00)
⚠ 注意：存在需求缺口，部分订单未满足。
═══════════════════ 求解统计 ═══════════════════
变量数：218
约束数：168
耗时：0.085 秒
═══════════════════ 分层优化汇总 ═══════════════════
层级 名称 松弛比例 最优值 包含KPI
1 需求满足 0% 19500.00 需求缺口
2 产能约束 0% 0.00 产能超载
3 业务KPI 5% 6405.00 批次偏差, 目标库存偏差, 供应目标偏差, 销售优先级
4 软约束 10% 190.00 超库存, 欠库存, 最小供应不足, 最大供应超出
--- 最终 KPI 值 (加权总惩罚) ---
加权总惩罚: 26415.25
需求缺口: 19500.00 (权重100 × 195.00)
产能超载: 0.00 (权重20 × 0.00)
批次偏差: 5124.27 (权重10 × 512.43)
目标库存偏差: 1432.35 (权重8 × 179.04)
供应目标偏差: 643.62 (权重8 × 80.45)
超库存: 0.00 (权重5 × 0.00)
欠库存: 190.00 (权重5 × 38.00)
最小供应不足: 0.00 (权重5 × 0.00)
最大供应超出: 0.00 (权重5 × 0.00)
销售优先级(负): 475.00 (权重1 × 475.00)
15:49:47.930 [main] INFO com.aps.service.plan.SceneService - 保存成功，场景ID: 1, 文件: F:\product\MES\hyh.apsj\mp\result\optimization_result_1.json
[OK] 优化结果JSON已导出: true Process finished with exit code 0
=== 运行结束 ===
mp/lp/model.lp
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mp/result/optimization_result_1.json
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src/main/java/com/aps/macroplanner/MacroPlannerOptimizer.java
View file @ e3a2cdde
package com.aps.macroplanner; package com.aps.macroplanner;
import com.aps.common.util.FileHelper;
import com.google.ortools.Loader; import com.google.ortools.Loader;
import com.google.ortools.linearsolver.MPSolver; import com.google.ortools.linearsolver.MPSolver;
import com.aps.macroplanner.constraint.ConstraintFactory; import com.aps.macroplanner.constraint.ConstraintFactory;
...@@ -89,7 +90,7 @@ public class MacroPlannerOptimizer { ...@@ -89,7 +90,7 @@ public class MacroPlannerOptimizer {
private static final String LP_FILE_PATH = LOG_DIR + "/lp/model.lp"; private static final String LP_FILE_PATH = LOG_DIR + "/lp/model.lp";
/** 运行日志文件路径 */ /** 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)。 */ /** 获取模型容器 (供 ResultWriter 等外部组件使用)。 */
public MacroPlannerModel getModel() { return model; } public MacroPlannerModel getModel() { return model; }
...@@ -148,6 +149,11 @@ public class MacroPlannerOptimizer { ...@@ -148,6 +149,11 @@ public class MacroPlannerOptimizer {
rootLogger.addHandler(handler); rootLogger.addHandler(handler);
} }
private void writeLog(String msg)
{
FileHelper.writeFile(msg,LOG_FILE_PATH,"log.txt");
}
// ==================== 模型构建流程 ==================== // ==================== 模型构建流程 ====================
/** /**
...@@ -163,32 +169,32 @@ public class MacroPlannerOptimizer { ...@@ -163,32 +169,32 @@ public class MacroPlannerOptimizer {
// 设为 FINE 可输出每个周期的折算详情 // 设为 FINE 可输出每个周期的折算详情
configureLogging(); 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) // 0. 数据完整性检查 (在构建模型前验证)
DataValidator validator = new DataValidator(data); DataValidator validator = new DataValidator(data);
if (!validator.validate()) { 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 { } 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 // 1. 决策变量
VariableFactory.createAll(model, data); 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) // 2. 约束 + KPI 汇总 (由 ConstraintFactory 统一调度)
ConstraintFactory.buildAll(model, data); 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) // 3. 目标函数 (加权求和)
ObjectiveBuilder.build(model, data); 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 // 4. 导出 LP 模型文件
exportLpModel(); 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"); + ", 约束=" + model.getSolver().numConstraints() + "\n");
} }
...@@ -211,9 +217,9 @@ public class MacroPlannerOptimizer { ...@@ -211,9 +217,9 @@ public class MacroPlannerOptimizer {
String lpContent = model.getSolver().exportModelAsLpFormat(); String lpContent = model.getSolver().exportModelAsLpFormat();
Path lpPath = Paths.get(LP_FILE_PATH).toAbsolutePath(); Path lpPath = Paths.get(LP_FILE_PATH).toAbsolutePath();
Files.write(lpPath, lpContent.getBytes(StandardCharsets.UTF_8)); 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) { } 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 { ...@@ -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> * 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() { public void solve() {
System.out.println("=== 开始分层求解 ===\n"); writeLog("=== 开始分层求解 ===\n");
startTimeMs = System.currentTimeMillis(); startTimeMs = System.currentTimeMillis();
KPIWeights w = data.getKpiWeights(); KPIWeights w = data.getKpiWeights();
...@@ -300,17 +306,20 @@ public class MacroPlannerOptimizer { ...@@ -300,17 +306,20 @@ public class MacroPlannerOptimizer {
if (i < levels.size() - 1 && level.getRelativeGoalSlack() >= 0.0) { if (i < levels.size() - 1 && level.getRelativeGoalSlack() >= 0.0) {
ObjectiveBuilder.addLevelBoundConstraint(model, level, optimalValue); ObjectiveBuilder.addLevelBoundConstraint(model, level, optimalValue);
System.out.printf(" 已添加边界约束: 上层目标 ≤ %.2f%n", 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 // 输出最终结果
MPSolver.ResultStatus finalStatus = model.getSolver().solve(); MPSolver.ResultStatus finalStatus = model.getSolver().solve();
if (finalStatus == MPSolver.ResultStatus.OPTIMAL if (finalStatus == MPSolver.ResultStatus.OPTIMAL
|| finalStatus == MPSolver.ResultStatus.FEASIBLE) { || finalStatus == MPSolver.ResultStatus.FEASIBLE) {
SolutionPrinter printer = new SolutionPrinter(model, data, startTimeMs); SolutionPrinter printer = new SolutionPrinter(model, data, startTimeMs,LOG_FILE_PATH);
printer.printAll(); printer.printAll();
// 构建层级最优值列表 // 构建层级最优值列表
List<Double> levelObjValues = new ArrayList<>(); List<Double> levelObjValues = new ArrayList<>();
...@@ -323,10 +332,10 @@ public class MacroPlannerOptimizer { ...@@ -323,10 +332,10 @@ public class MacroPlannerOptimizer {
ResultWriter rw = new ResultWriter(model, data, startTimeMs); ResultWriter rw = new ResultWriter(model, data, startTimeMs);
boolean jsonPath = rw.saveResultToFile("1"); boolean jsonPath = rw.saveResultToFile("1");
if (jsonPath) { 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 { } 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 { ...@@ -135,7 +135,7 @@ public class InventorySpecConstraint {
} else { } else {
double rhs = spec.getTargetLevel(); double rhs = spec.getTargetLevel();
MPConstraint c = model.getSolver().makeConstraint( MPConstraint c = model.getSolver().makeConstraint(
rhs, rhs, "TargetInv_" + invKey); rhs, MPSolver.infinity(), "TargetInv_" + invKey);
c.setCoefficient(invVar, 1.0); c.setCoefficient(invVar, 1.0);
MPVariable u = targetUnderVars.get(invKey); MPVariable u = targetUnderVars.get(invKey);
if (u != null) c.setCoefficient(u, 1.0); 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.*; ...@@ -5,6 +5,7 @@ import com.aps.entity.*;
import com.aps.entity.basic.Material; import com.aps.entity.basic.Material;
import com.aps.entity.basic.MaterialSupply; import com.aps.entity.basic.MaterialSupply;
import com.aps.mapper.EquipShiftCapacityMapper; import com.aps.mapper.EquipShiftCapacityMapper;
import com.baomidou.mybatisplus.extension.plugins.pagination.Page;
import com.fasterxml.jackson.core.type.TypeReference; import com.fasterxml.jackson.core.type.TypeReference;
import com.fasterxml.jackson.databind.ObjectMapper; import com.fasterxml.jackson.databind.ObjectMapper;
import com.aps.mapper.EquipinfoMapper; import com.aps.mapper.EquipinfoMapper;
...@@ -190,6 +191,16 @@ public class MacroPlannerDataConverter { ...@@ -190,6 +191,16 @@ public class MacroPlannerDataConverter {
new LambdaQueryWrapper<ApsDemandOrder>() new LambdaQueryWrapper<ApsDemandOrder>()
.ge(ApsDemandOrder::getDeliverytime, ctx.baseTime) .ge(ApsDemandOrder::getDeliverytime, ctx.baseTime)
.lt(ApsDemandOrder::getDeliverytime, horizonEndDateTime)); .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()); 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) // 2. 收集 materialIds (从 ApsDemandOrder.mmid)
...@@ -215,6 +226,40 @@ public class MacroPlannerDataConverter { ...@@ -215,6 +226,40 @@ public class MacroPlannerDataConverter {
// 4. 工序 (通过 LanuchService 批量查询) // 4. 工序 (通过 LanuchService 批量查询)
if (!routingIds.isEmpty()) { 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() List<Long> routingIdsLong = routingIds.stream()
.map(Long::valueOf) .map(Long::valueOf)
.collect(Collectors.toList()); .collect(Collectors.toList());
...@@ -237,9 +282,12 @@ public class MacroPlannerDataConverter { ...@@ -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) // 6. 收集所有 materialId (订单 + 工艺物料消耗 + 工艺路线头表)
ctx.routingsupportings.forEach(rs -> { ctx.routingsupportings.forEach(rs -> {
if (rs.getMaterialId() != null) materialIds.add(rs.getMaterialId()); if (rs.getMaterialId() != null) materialIds.add(rs.getMaterialId());
}); });
// 7. 物料主数据 // 7. 物料主数据
...@@ -641,7 +689,7 @@ public class MacroPlannerDataConverter { ...@@ -641,7 +689,7 @@ public class MacroPlannerDataConverter {
// 3.1 为每个 Material 创建 Product // 3.1 为每个 Material 创建 Product
for (Material m : ctx.materialByMaterialId.values()) { for (Material m : ctx.materialByMaterialId.values()) {
String name = pickName(m.getName(), m.getCode(), m.getId()); 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); products.add(p);
ctx.productByMaterialId.put(m.getId(), p); ctx.productByMaterialId.put(m.getId(), p);
} }
...@@ -892,10 +940,10 @@ public class MacroPlannerDataConverter { ...@@ -892,10 +940,10 @@ public class MacroPlannerDataConverter {
if (inputMaterial == null) { if (inputMaterial == null) {
continue; continue;
} }
if (!"MP".equals(inputMaterial.getMaterialTypeName())) { // if (!"MP".equals(inputMaterial.getMaterialTypeName())) {
// 半成品/成品不作为投料, 由各自 Routing 产出 // // 半成品/成品不作为投料, 由各自 Routing 产出
continue; // continue;
} // }
if (rs.getMainQty() == null || rs.getMainQty().compareTo(BigDecimal.ZERO) == 0) { if (rs.getMainQty() == null || rs.getMainQty().compareTo(BigDecimal.ZERO) == 0) {
log.warn("跳过主量为0的BOM项: routingDetailId={}, materialId={}", log.warn("跳过主量为0的BOM项: routingDetailId={}, materialId={}",
...@@ -919,9 +967,11 @@ public class MacroPlannerDataConverter { ...@@ -919,9 +967,11 @@ public class MacroPlannerDataConverter {
// - 有 MATERIAL_PURCHASE → 每供应商一个 Operation, leadTimeDays = purchaseCycle // - 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 // - 无 MATERIAL_PURCHASE → 通用供应商 unit, relativeDuration=1, leadTimeDays=0, UnitPeriod 无限
for (Material m : ctx.materialByMaterialId.values()) { for (Material m : ctx.materialByMaterialId.values()) {
if (!"MP".equals(m.getMaterialTypeName())) { long headercount= ctx.routingHeaders.stream().filter(t->t.getMaterialId()==m.getId()).count();
continue; if(headercount>0)
} {
continue;
}
Product p = ctx.productByMaterialId.get(m.getId()); Product p = ctx.productByMaterialId.get(m.getId());
if (p == null) { if (p == null) {
continue; continue;
...@@ -1287,7 +1337,7 @@ public class MacroPlannerDataConverter { ...@@ -1287,7 +1337,7 @@ public class MacroPlannerDataConverter {
String key = m.getProduct().getId() + "_" + m.getStockingPoint().getId() + "_" + p.getIndex(); String key = m.getProduct().getId() + "_" + m.getStockingPoint().getId() + "_" + p.getIndex();
if (invSpecKeys.add(key)) { if (invSpecKeys.add(key)) {
inventorySpecs.add(new InventorySpec(m.getProduct(), m.getStockingPoint(), p, 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 { ...@@ -1305,7 +1355,7 @@ public class MacroPlannerDataConverter {
for (Operation op : operations) { for (Operation op : operations) {
if (op.getId().startsWith("OP_PROCURE_")) { if (op.getId().startsWith("OP_PROCURE_")) {
supplySpecs.add(new SupplySpec("Supply-" + op.getId(), 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()); 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 { ...@@ -112,7 +112,21 @@ public class ObjectiveBuilder {
// 设置为最小化目标 // 设置为最小化目标
objective.setMinimization(); 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 ==================== // ==================== 分层优化方法 ====================
/** /**
...@@ -165,7 +179,7 @@ public class ObjectiveBuilder { ...@@ -165,7 +179,7 @@ public class ObjectiveBuilder {
* *
* <h3>数学公式</h3> * <h3>数学公式</h3>
* <pre> * <pre>
* Σ (effectiveCoeff × KPI_variable) ≤ optimalValue × (1 + relativeGoalSlack) * Σ (effectiveCoeff × KPI_variable) ≤ optimalValue + |optimalValue| × relativeGoalSlack
* </pre> * </pre>
* *
* @param model 模型容器 * @param model 模型容器
...@@ -178,7 +192,7 @@ public class ObjectiveBuilder { ...@@ -178,7 +192,7 @@ public class ObjectiveBuilder {
if (level.getRelativeGoalSlack() < 0.0) return; // 负松弛表示不约束 if (level.getRelativeGoalSlack() < 0.0) return; // 负松弛表示不约束
MPSolver solver = model.getSolver(); MPSolver solver = model.getSolver();
double upperBound = optimalValue * (1.0 + level.getRelativeGoalSlack()); double upperBound = computeUpperBound(optimalValue, level.getRelativeGoalSlack());
MPConstraint bound = solver.makeConstraint( MPConstraint bound = solver.makeConstraint(
-MPSolver.infinity(), upperBound, -MPSolver.infinity(), upperBound,
......
src/main/java/com/aps/macroplanner/output/SolutionPrinter.java
View file @ e3a2cdde
package com.aps.macroplanner.output; package com.aps.macroplanner.output;
import com.aps.common.util.FileHelper;
import com.aps.macroplanner.data.*; import com.aps.macroplanner.data.*;
import com.aps.macroplanner.model.MacroPlannerModel; import com.aps.macroplanner.model.MacroPlannerModel;
import com.aps.macroplanner.objective.StrategyLevel; import com.aps.macroplanner.objective.StrategyLevel;
...@@ -30,12 +31,25 @@ public class SolutionPrinter { ...@@ -30,12 +31,25 @@ public class SolutionPrinter {
private final TestDataBuilder data; private final TestDataBuilder data;
private final long startTimeMs; private final long startTimeMs;
public SolutionPrinter(MacroPlannerModel model, TestDataBuilder data, long startTimeMs) { private final String LOG_FILE_PATH;
public SolutionPrinter(MacroPlannerModel model, TestDataBuilder data, long startTimeMs,String logfilepath) {
this.model = model; this.model = model;
this.data = data; this.data = data;
this.startTimeMs = startTimeMs; this.startTimeMs = startTimeMs;
this.LOG_FILE_PATH=logfilepath;
}
private void writeLog(String msg)
{
FileHelper.writeFile(msg,LOG_FILE_PATH,"log.txt");
} }
private void writeLog(String format, Object ... args)
{
writeLog(String.format(format,args));
}
// ==================== 主入口 ==================== // ==================== 主入口 ====================
/** 输出完整求解结果 */ /** 输出完整求解结果 */
...@@ -50,14 +64,14 @@ public class SolutionPrinter { ...@@ -50,14 +64,14 @@ public class SolutionPrinter {
// ==================== BOM 关系验证 ==================== // ==================== BOM 关系验证 ====================
private void printBomStructure() { private void printBomStructure() {
System.out.println("📋 BOM关系验证:"); writeLog("📋 BOM关系验证:");
for (Product prod : data.getProducts()) { for (Product prod : data.getProducts()) {
System.out.printf(" %s → 消耗: %s, 被消耗于: %s%n", writeLog(" %s → 消耗: %s, 被消耗于: %s",
prod.getId(), prod.getId(),
formatConsumes(prod), formatConsumes(prod),
formatConsumedBy(prod)); formatConsumedBy(prod));
} }
System.out.println(); writeLog("");
} }
/** 某产品消耗了哪些物料 (BOM输入, 含库存点) */ /** 某产品消耗了哪些物料 (BOM输入, 含库存点) */
...@@ -73,7 +87,7 @@ public class SolutionPrinter { ...@@ -73,7 +87,7 @@ public class SolutionPrinter {
inputCount++; inputCount++;
} }
if (inputCount > 0) { if (inputCount > 0) {
LOG.fine(String.format("[结果输出] BOM消耗: '%s'(产出%s) 消耗 %d 种物料", writeLog(String.format("[结果输出] BOM消耗: '%s'(产出%s) 消耗 %d 种物料",
op.getId(), formatOutputProducts(op), inputCount)); op.getId(), formatOutputProducts(op), inputCount));
} }
} }
...@@ -88,7 +102,7 @@ public class SolutionPrinter { ...@@ -88,7 +102,7 @@ public class SolutionPrinter {
// 遍历消费者工序的所有产出 (支持联产品/副产品) // 遍历消费者工序的所有产出 (支持联产品/副产品)
List<OperationOutput> outputs = input.getOperation().getOutputs(); List<OperationOutput> outputs = input.getOperation().getOutputs();
if (outputs.size() > 1) { if (outputs.size() > 1) {
LOG.fine(String.format("[结果输出] 多产出消耗: '%s' 被工序 '%s' 消耗, 该工序有 %d 个产出", writeLog(String.format("[结果输出] 多产出消耗: '%s' 被工序 '%s' 消耗, 该工序有 %d 个产出",
prod.getId(), input.getOperation().getId(), outputs.size())); prod.getId(), input.getOperation().getId(), outputs.size()));
} }
for (OperationOutput oo : outputs) { for (OperationOutput oo : outputs) {
...@@ -106,7 +120,7 @@ public class SolutionPrinter { ...@@ -106,7 +120,7 @@ public class SolutionPrinter {
ids.add(oo.getProductId()); ids.add(oo.getProductId());
} }
if (ids.size() > 1) { if (ids.size() > 1) {
LOG.fine(String.format("[结果输出] 多产出工序 '%s': 产出=%s", writeLog(String.format("[结果输出] 多产出工序 '%s': 产出=%s",
op.getId(), String.join("+", ids))); op.getId(), String.join("+", ids)));
} }
return ids.isEmpty() ? "-" : String.join("+", ids); return ids.isEmpty() ? "-" : String.join("+", ids);
...@@ -148,25 +162,25 @@ public class SolutionPrinter { ...@@ -148,25 +162,25 @@ public class SolutionPrinter {
} }
} }
System.out.println("========== 网状BOM + MRP 排产求解 =========="); writeLog("========== 网状BOM + MRP 排产求解 ==========");
System.out.printf("成品(根节点) %d 种：%s%n", finishedGoods.size(), writeLog("成品(根节点) %d 种：%s", finishedGoods.size(),
String.join(" ", finishedGoods)); String.join(" ", finishedGoods));
System.out.printf("生产品 %d 种：%s%n", producedGoods.size(), writeLog("生产品 %d 种：%s", producedGoods.size(),
String.join(" ", producedGoods)); String.join(" ", producedGoods));
if (!rawMaterials.isEmpty()) { if (!rawMaterials.isEmpty()) {
System.out.printf("采购品 %d 种：%s%n", rawMaterials.size(), writeLog("采购品 %d 种：%s", rawMaterials.size(),
String.join(" ", rawMaterials)); String.join(" ", rawMaterials));
} }
System.out.printf("周期 %d 天%n", data.getPeriods().size()); writeLog("周期 %d 天", data.getPeriods().size());
System.out.println(); writeLog("-------------");
} }
// ==================== 每日视图 ==================== // ==================== 每日视图 ====================
private void printDailyViews() { private void printDailyViews() {
for (Period p : data.getPeriods()) { for (Period p : data.getPeriods()) {
System.out.println(); writeLog(" ");
System.out.printf("═══════════════════ 第 %d 天 ═══════════════════%n", writeLog("═══════════════════ 第 %d 天 ═══════════════════",
p.getIndex() + 1); p.getIndex() + 1);
printLineView(p); printLineView(p);
printProductView(p); printProductView(p);
...@@ -178,7 +192,7 @@ public class SolutionPrinter { ...@@ -178,7 +192,7 @@ public class SolutionPrinter {
// --- 产线视图 --- // --- 产线视图 ---
private void printLineView(Period p) { private void printLineView(Period p) {
System.out.println(" ▶ 产线视图（按产线分组）"); writeLog(" ▶ 产线视图（按产线分组）");
// 收集所有 unit // 收集所有 unit
Set<String> unitIds = new LinkedHashSet<>(); Set<String> unitIds = new LinkedHashSet<>();
...@@ -193,10 +207,10 @@ public class SolutionPrinter { ...@@ -193,10 +207,10 @@ public class SolutionPrinter {
if (up == null) continue; if (up == null) continue;
if (up.isUnlimited()) { if (up.isUnlimited()) {
System.out.printf(" 【%s】产能无限 (供应商)%n", unitId); writeLog(" 【%s】产能无限 (供应商)", unitId);
} else { } else {
String minStr = up.hasMinCapacity() ? String.format("最小%.0fh/", up.getMinCapacity()) : ""; String minStr = up.hasMinCapacity() ? String.format("最小%.0fh/", up.getMinCapacity()) : "";
System.out.printf(" 【%s】产能%s%.0fh %s%n", unitId, minStr, up.getMaxCapacity(), writeLog(" 【%s】产能%s%.0fh %s", unitId, minStr, up.getMaxCapacity(),
up.hasMinCapacity() ? "(强制最小)" : ""); up.hasMinCapacity() ? "(强制最小)" : "");
} }
...@@ -210,22 +224,22 @@ public class SolutionPrinter { ...@@ -210,22 +224,22 @@ public class SolutionPrinter {
hasProduction = true; hasProduction = true;
double capacityUsed = ptQty * uo.getCapacityCoeff(); double capacityUsed = ptQty * uo.getCapacityCoeff();
if (up.isUnlimited()) { if (up.isUnlimited()) {
System.out.printf(" %s(%s): %.0f件 (耗时%.1fh)%n", writeLog(" %s(%s): %.0f件 (耗时%.1fh)",
op.getName(), formatOutputProducts(op), ptQty, capacityUsed); op.getName(), formatOutputProducts(op), ptQty, capacityUsed);
} else { } else {
double utilPercent = up.getMaxCapacity() > 0 double utilPercent = up.getMaxCapacity() > 0
? capacityUsed / up.getMaxCapacity() * 100 : 0; ? capacityUsed / up.getMaxCapacity() * 100 : 0;
System.out.printf(" %s(%s): %.0f件 (耗时%.1fh) %s%n", writeLog(" %s(%s): %.0f件 (耗时%.1fh) %s",
op.getName(), formatOutputProducts(op), ptQty, capacityUsed, op.getName(), formatOutputProducts(op), ptQty, capacityUsed,
uo.hasLotSize() ? String.format(", 批次%.0f", uo.getLotSize()) : ""); uo.hasLotSize() ? String.format(", 批次%.0f", uo.getLotSize()) : "");
System.out.printf(" 利用率: %.0f/%.0f h (%.0f%%)%n", writeLog(" 利用率: %.0f/%.0f h (%.0f%%)",
capacityUsed, up.getMaxCapacity(), utilPercent); capacityUsed, up.getMaxCapacity(), utilPercent);
} }
} }
} }
} }
if (!hasProduction) { if (!hasProduction) {
System.out.println(" （休息）"); writeLog(" （休息）");
} }
} }
} }
...@@ -233,7 +247,7 @@ public class SolutionPrinter { ...@@ -233,7 +247,7 @@ public class SolutionPrinter {
// --- 产品视图 --- // --- 产品视图 ---
private void printProductView(Period p) { private void printProductView(Period p) {
System.out.println(" ▶ 产品视图（汇总各产线产量）"); writeLog(" ▶ 产品视图（汇总各产线产量）");
for (Product prod : data.getProducts()) { for (Product prod : data.getProducts()) {
for (StockingPoint sp : data.getStockingPointsForProduct(prod.getId())) { for (StockingPoint sp : data.getStockingPointsForProduct(prod.getId())) {
...@@ -284,7 +298,7 @@ public class SolutionPrinter { ...@@ -284,7 +298,7 @@ public class SolutionPrinter {
} }
} }
if (matchedUnitOpCount > 1) { if (matchedUnitOpCount > 1) {
LOG.fine(String.format("[结果输出] 多Unit产出: %s@%s P%d 有 %d 个UnitOp产出到该库存点 (到货=%.0f, 生产中=%.0f)", writeLog(String.format("[结果输出] 多Unit产出: %s@%s P%d 有 %d 个UnitOp产出到该库存点 (到货=%.0f, 生产中=%.0f)",
prod.getId(), sp.getId(), p.getIndex(), matchedUnitOpCount, prod.getId(), sp.getId(), p.getIndex(), matchedUnitOpCount,
totalArrived, totalInProduction)); totalArrived, totalInProduction));
} }
...@@ -318,7 +332,7 @@ public class SolutionPrinter { ...@@ -318,7 +332,7 @@ public class SolutionPrinter {
? String.format("期初库存%.0f件 → ", openingInv) ? String.format("期初库存%.0f件 → ", openingInv)
: String.format("上期库存%.0f件 → ", openingInv); : String.format("上期库存%.0f件 → ", openingInv);
System.out.printf(" %s@%s: %s期末库存%.0f件 %s | %s%s%s | 销售%.0f/%.0f件", writeLog(" %s@%s: %s期末库存%.0f件 %s | %s%s%s | 销售%.0f/%.0f件",
prod.getId(), sp.getId(), openingStr, invQty, specStr, prod.getId(), sp.getId(), openingStr, invQty, specStr,
totalArrived > 0.001 totalArrived > 0.001
? "到货共" + formatNum(totalArrived) + "件 [" ? "到货共" + formatNum(totalArrived) + "件 ["
...@@ -333,11 +347,11 @@ public class SolutionPrinter { ...@@ -333,11 +347,11 @@ public class SolutionPrinter {
double unmet = totalDemand - totalSales; double unmet = totalDemand - totalSales;
if (unmet > 0.001) { if (unmet > 0.001) {
System.out.printf(" ⚠未满足%.0f件", unmet); writeLog(" ⚠未满足%.0f件", unmet);
// 分析未满足原因 // 分析未满足原因
System.out.print(" " + analyzeUnmetReason(prod, sp, p, openingInv, totalArrived, unmet)); writeLog(" " + analyzeUnmetReason(prod, sp, p, openingInv, totalArrived, unmet));
} }
System.out.println();
} }
} }
} }
...@@ -459,7 +473,7 @@ public class SolutionPrinter { ...@@ -459,7 +473,7 @@ public class SolutionPrinter {
// --- 物料需求展开 --- // --- 物料需求展开 ---
private void printBomExplosion(Period p) { private void printBomExplosion(Period p) {
System.out.println(" ▶ 物料需求展开（按BOM逐级展开）"); writeLog(" ▶ 物料需求展开（按BOM逐级展开）");
for (Operation op : data.getOperations()) { for (Operation op : data.getOperations()) {
// 跨 UnitOperations 求和总产量 // 跨 UnitOperations 求和总产量
...@@ -471,7 +485,7 @@ public class SolutionPrinter { ...@@ -471,7 +485,7 @@ public class SolutionPrinter {
if (ptQty < 0.001) continue; if (ptQty < 0.001) continue;
String outputLabel = formatOutputProducts(op); String outputLabel = formatOutputProducts(op);
System.out.printf(" %s(%s)生产%.0f件 →%n", op.getName(), outputLabel, ptQty); writeLog(" %s(%s)生产%.0f件 →", op.getName(), outputLabel, ptQty);
// 找到该操作的所有输入物料 // 找到该操作的所有输入物料
int inputMatched = 0; int inputMatched = 0;
...@@ -508,7 +522,7 @@ public class SolutionPrinter { ...@@ -508,7 +522,7 @@ public class SolutionPrinter {
} }
} }
if (matchedInputOps > 1) { if (matchedInputOps > 1) {
LOG.fine(String.format("[结果输出] 物料多源生产: %s@%s P%d 有 %d 个工序产出 (总量=%.0f)", writeLog(String.format("[结果输出] 物料多源生产: %s@%s P%d 有 %d 个工序产出 (总量=%.0f)",
inputProd.getId(), inputSp.getId(), p.getIndex(), inputProd.getId(), inputSp.getId(), p.getIndex(),
matchedInputOps, inputProdQty)); matchedInputOps, inputProdQty));
} }
...@@ -536,18 +550,18 @@ public class SolutionPrinter { ...@@ -536,18 +550,18 @@ public class SolutionPrinter {
String inTransitNote = inTransit > 0.001 String inTransitNote = inTransit > 0.001
? String.format("(+在途%.0f)", inTransit) : ""; ? String.format("(+在途%.0f)", inTransit) : "";
System.out.printf(" ─── 物料需求汇总 ───%n"); writeLog(" ─── 物料需求汇总 ───");
System.out.printf(" %s(%s): 期初库存%.0f件, 今日生产%.0f件%s, 今日需求%.0f件, 期末库存%.0f件%n", writeLog(" %s(%s): 期初库存%.0f件, 今日生产%.0f件%s, 今日需求%.0f件, 期末库存%.0f件",
inputProd.getId(), inputProd.getId(),
inputProd.getId().startsWith("R") ? "采购" : "生产", inputProd.getId().startsWith("R") ? "采购" : "生产",
prevInv, inputProdQty, inTransitNote, prevInv, inputProdQty, inTransitNote,
opDemand + externalSales, endInv); opDemand + externalSales, endInv);
System.out.printf(" └ %s需求%.0f件(由%s×%s系数)%n", writeLog(" └ %s需求%.0f件(由%s×%s系数)",
inputProd.getId(), opDemand, inputProd.getId(), opDemand,
formatOutputProducts(op), formatFactor(input.getFactor())); formatOutputProducts(op), formatFactor(input.getFactor()));
} }
if (inputMatched == 0) { if (inputMatched == 0) {
LOG.fine(String.format("[结果输出] 无BOM输入: '%s'(产出=%s) P%d 生产%.0f件, 无物料消耗", writeLog(String.format("[结果输出] 无BOM输入: '%s'(产出=%s) P%d 生产%.0f件, 无物料消耗",
op.getId(), outputLabel, p.getIndex(), ptQty)); op.getId(), outputLabel, p.getIndex(), ptQty));
} }
} }
...@@ -556,7 +570,7 @@ public class SolutionPrinter { ...@@ -556,7 +570,7 @@ public class SolutionPrinter {
// --- 期末库存 --- // --- 期末库存 ---
private void printEndingInventory(Period p) { private void printEndingInventory(Period p) {
System.out.print(" ▶ 期末库存"); writeLog(" ▶ 期末库存");
// 收集所有产品在本周期的库存 // 收集所有产品在本周期的库存
List<String> items = new ArrayList<>(); List<String> items = new ArrayList<>();
for (Product prod : data.getProducts()) { for (Product prod : data.getProducts()) {
...@@ -566,16 +580,16 @@ public class SolutionPrinter { ...@@ -566,16 +580,16 @@ public class SolutionPrinter {
items.add(String.format("%s@%s=%.0f", prod.getId(), sp.getId(), invQty)); items.add(String.format("%s@%s=%.0f", prod.getId(), sp.getId(), invQty));
} }
} }
System.out.println(" " + String.join(" ", items)); writeLog(" " + String.join(" ", items));
} }
// ==================== KPI 汇总 ==================== // ==================== KPI 汇总 ====================
private void printKpiSummary() { private void printKpiSummary() {
System.out.println();
System.out.println("═══════════════════ KPI 汇总 ═══════════════════"); writeLog("═══════════════════ KPI 汇总 ═══════════════════");
double objValue = model.getSolver().objective().value(); double objValue = model.getSolver().objective().value();
System.out.printf("目标函数值 (最小总惩罚): %.2f%n", objValue); writeLog("目标函数值 (最小总惩罚): %.2f", objValue);
double fulfillment = model.getTotalFulfillment().solutionValue(); double fulfillment = model.getTotalFulfillment().solutionValue();
double lotSize = model.getTotalLotSize().solutionValue(); double lotSize = model.getTotalLotSize().solutionValue();
...@@ -589,31 +603,31 @@ public class SolutionPrinter { ...@@ -589,31 +603,31 @@ public class SolutionPrinter {
double salesPriority = model.getTotalSalesDemandPriority().solutionValue(); double salesPriority = model.getTotalSalesDemandPriority().solutionValue();
KPIWeights w = data.getKpiWeights(); KPIWeights w = data.getKpiWeights();
System.out.printf("需求缺口惩罚: %.2f (权重%.0f × %.2f)%n", writeLog("需求缺口惩罚: %.2f (权重%.0f × %.2f)",
fulfillment * w.getFulfillmentWeight(), w.getFulfillmentWeight(), fulfillment); fulfillment * w.getFulfillmentWeight(), w.getFulfillmentWeight(), fulfillment);
System.out.printf("批次偏差惩罚: %.2f (权重%.0f × %.2f)%n", writeLog("批次偏差惩罚: %.2f (权重%.0f × %.2f)",
lotSize * w.getLotSizeWeight(), w.getLotSizeWeight(), lotSize); lotSize * w.getLotSizeWeight(), w.getLotSizeWeight(), lotSize);
System.out.printf("超库存惩罚: %.2f (权重%.0f × %.2f)%n", writeLog("超库存惩罚: %.2f (权重%.0f × %.2f)",
maxInv * w.getMaxInventoryLevelWeight(), w.getMaxInventoryLevelWeight(), maxInv); maxInv * w.getMaxInventoryLevelWeight(), w.getMaxInventoryLevelWeight(), maxInv);
System.out.printf("欠库存惩罚: %.2f (权重%.0f × %.2f)%n", writeLog("欠库存惩罚: %.2f (权重%.0f × %.2f)",
minInv * w.getMinInventoryLevelWeight(), w.getMinInventoryLevelWeight(), minInv); minInv * w.getMinInventoryLevelWeight(), w.getMinInventoryLevelWeight(), minInv);
System.out.printf("目标库存偏差: %.2f (权重%.0f × %.2f)%n", writeLog("目标库存偏差: %.2f (权重%.0f × %.2f)",
targetInv * w.getTargetInventoryLevelWeight(), w.getTargetInventoryLevelWeight(), targetInv); targetInv * w.getTargetInventoryLevelWeight(), w.getTargetInventoryLevelWeight(), targetInv);
System.out.printf("产能超载惩罚: %.2f (权重%.0f × %.2f)%n", writeLog("产能超载惩罚: %.2f (权重%.0f × %.2f)",
capacity * w.getUnitCapacityWeight(), w.getUnitCapacityWeight(), capacity); capacity * w.getUnitCapacityWeight(), w.getUnitCapacityWeight(), capacity);
System.out.printf("供应目标偏差: %.2f (权重%.0f × %.2f)%n", writeLog("供应目标偏差: %.2f (权重%.0f × %.2f)",
supplyTarget * w.getSupplyTargetWeight(), w.getSupplyTargetWeight(), supplyTarget); supplyTarget * w.getSupplyTargetWeight(), w.getSupplyTargetWeight(), supplyTarget);
System.out.printf("最小供应不足: %.2f (权重%.0f × %.2f)%n", writeLog("最小供应不足: %.2f (权重%.0f × %.2f)",
minSupply * w.getMinSupplyWeight(), w.getMinSupplyWeight(), minSupply); minSupply * w.getMinSupplyWeight(), w.getMinSupplyWeight(), minSupply);
System.out.printf("最大供应超出: %.2f (权重%.0f × %.2f)%n", writeLog("最大供应超出: %.2f (权重%.0f × %.2f)",
maxSupply * w.getMaxSupplyWeight(), w.getMaxSupplyWeight(), maxSupply); maxSupply * w.getMaxSupplyWeight(), w.getMaxSupplyWeight(), maxSupply);
System.out.printf("销售优先级(负): %.2f (权重%.0f × %.2f)%n", writeLog("销售优先级(负): %.2f (权重%.0f × %.2f)",
salesPriority * w.getSalesDemandPriorityWeight(), salesPriority * w.getSalesDemandPriorityWeight(),
w.getSalesDemandPriorityWeight(), salesPriority); w.getSalesDemandPriorityWeight(), salesPriority);
if (fulfillment > 0.001) { if (fulfillment > 0.001) {
System.out.println();
System.out.println("⚠ 注意：存在需求缺口，部分订单未满足。"); writeLog("⚠ 注意：存在需求缺口，部分订单未满足。");
} }
} }
...@@ -621,12 +635,12 @@ public class SolutionPrinter { ...@@ -621,12 +635,12 @@ public class SolutionPrinter {
private void printStatistics() { private void printStatistics() {
long elapsedMs = System.currentTimeMillis() - startTimeMs; long elapsedMs = System.currentTimeMillis() - startTimeMs;
System.out.println(); writeLog("");
System.out.println("═══════════════════ 求解统计 ═══════════════════"); writeLog("═══════════════════ 求解统计 ═══════════════════");
System.out.printf("变量数：%d%n", model.getSolver().numVariables()); writeLog("变量数：%d", model.getSolver().numVariables());
System.out.printf("约束数：%d%n", model.getSolver().numConstraints()); writeLog("约束数：%d", model.getSolver().numConstraints());
System.out.printf("耗时：%.3f 秒%n", elapsedMs / 1000.0); writeLog("耗时：%.3f 秒", elapsedMs / 1000.0);
System.out.println();
} }
// ==================== 分层优化汇总 ==================== // ==================== 分层优化汇总 ====================
...@@ -643,11 +657,11 @@ public class SolutionPrinter { ...@@ -643,11 +657,11 @@ public class SolutionPrinter {
*/ */
public void printHierarchicalSummary(List<StrategyLevel> levels, public void printHierarchicalSummary(List<StrategyLevel> levels,
List<Double> levelObjValues) { List<Double> levelObjValues) {
System.out.println(); writeLog("");
System.out.println("═══════════════════ 分层优化汇总 ═══════════════════"); writeLog("═══════════════════ 分层优化汇总 ═══════════════════");
// 表头 // 表头
System.out.printf("%-6s %-14s %-12s %-12s %s%n", writeLog("%-6s %-14s %-12s %-12s %s",
"层级", "名称", "松弛比例", "最优值", "包含KPI"); "层级", "名称", "松弛比例", "最优值", "包含KPI");
double totalWeightedPenalty = 0.0; double totalWeightedPenalty = 0.0;
...@@ -663,7 +677,7 @@ public class SolutionPrinter { ...@@ -663,7 +677,7 @@ public class SolutionPrinter {
kpiNames.add(kpi.name); kpiNames.add(kpi.name);
} }
System.out.printf("%-6d %-14s %-12s %-12.2f %s%n", writeLog("%-6d %-14s %-12s %-12.2f %s",
level.getLevel(), level.getLevel(),
level.getName(), level.getName(),
String.format("%.0f%%", level.getRelativeGoalSlack() * 100), String.format("%.0f%%", level.getRelativeGoalSlack() * 100),
...@@ -672,8 +686,8 @@ public class SolutionPrinter { ...@@ -672,8 +686,8 @@ public class SolutionPrinter {
} }
// 计算并输出加权总惩罚 (等价于单目标函数值) // 计算并输出加权总惩罚 (等价于单目标函数值)
System.out.println(); writeLog("");
System.out.println("--- 最终 KPI 值 (加权总惩罚) ---"); writeLog("--- 最终 KPI 值 (加权总惩罚) ---");
double fulfillment = model.getTotalFulfillment().solutionValue(); double fulfillment = model.getTotalFulfillment().solutionValue();
double lotSize = model.getTotalLotSize().solutionValue(); double lotSize = model.getTotalLotSize().solutionValue();
double maxInv = model.getTotalMaxInventoryLevel().solutionValue(); double maxInv = model.getTotalMaxInventoryLevel().solutionValue();
...@@ -696,26 +710,26 @@ public class SolutionPrinter { ...@@ -696,26 +710,26 @@ public class SolutionPrinter {
+ maxSupply * w.getMaxSupplyWeight() + maxSupply * w.getMaxSupplyWeight()
- salesPriority * w.getSalesDemandPriorityWeight(); - salesPriority * w.getSalesDemandPriorityWeight();
System.out.printf(" 加权总惩罚: %.2f%n", totalPenalty); writeLog(" 加权总惩罚: %.2f", totalPenalty);
System.out.printf(" 需求缺口: %.2f (权重%.0f × %.2f)%n", writeLog(" 需求缺口: %.2f (权重%.0f × %.2f)",
fulfillment * w.getFulfillmentWeight(), w.getFulfillmentWeight(), fulfillment); fulfillment * w.getFulfillmentWeight(), w.getFulfillmentWeight(), fulfillment);
System.out.printf(" 产能超载: %.2f (权重%.0f × %.2f)%n", writeLog(" 产能超载: %.2f (权重%.0f × %.2f)",
capacity * w.getUnitCapacityWeight(), w.getUnitCapacityWeight(), capacity); capacity * w.getUnitCapacityWeight(), w.getUnitCapacityWeight(), capacity);
System.out.printf(" 批次偏差: %.2f (权重%.0f × %.2f)%n", writeLog(" 批次偏差: %.2f (权重%.0f × %.2f)",
lotSize * w.getLotSizeWeight(), w.getLotSizeWeight(), lotSize); lotSize * w.getLotSizeWeight(), w.getLotSizeWeight(), lotSize);
System.out.printf(" 目标库存偏差: %.2f (权重%.0f × %.2f)%n", writeLog(" 目标库存偏差: %.2f (权重%.0f × %.2f)",
targetInv * w.getTargetInventoryLevelWeight(), w.getTargetInventoryLevelWeight(), targetInv); targetInv * w.getTargetInventoryLevelWeight(), w.getTargetInventoryLevelWeight(), targetInv);
System.out.printf(" 供应目标偏差: %.2f (权重%.0f × %.2f)%n", writeLog(" 供应目标偏差: %.2f (权重%.0f × %.2f)",
supplyTarget * w.getSupplyTargetWeight(), w.getSupplyTargetWeight(), supplyTarget); supplyTarget * w.getSupplyTargetWeight(), w.getSupplyTargetWeight(), supplyTarget);
System.out.printf(" 超库存: %.2f (权重%.0f × %.2f)%n", writeLog(" 超库存: %.2f (权重%.0f × %.2f)",
maxInv * w.getMaxInventoryLevelWeight(), w.getMaxInventoryLevelWeight(), maxInv); maxInv * w.getMaxInventoryLevelWeight(), w.getMaxInventoryLevelWeight(), maxInv);
System.out.printf(" 欠库存: %.2f (权重%.0f × %.2f)%n", writeLog(" 欠库存: %.2f (权重%.0f × %.2f)",
minInv * w.getMinInventoryLevelWeight(), w.getMinInventoryLevelWeight(), minInv); minInv * w.getMinInventoryLevelWeight(), w.getMinInventoryLevelWeight(), minInv);
System.out.printf(" 最小供应不足: %.2f (权重%.0f × %.2f)%n", writeLog(" 最小供应不足: %.2f (权重%.0f × %.2f)",
minSupply * w.getMinSupplyWeight(), w.getMinSupplyWeight(), minSupply); minSupply * w.getMinSupplyWeight(), w.getMinSupplyWeight(), minSupply);
System.out.printf(" 最大供应超出: %.2f (权重%.0f × %.2f)%n", writeLog(" 最大供应超出: %.2f (权重%.0f × %.2f)",
maxSupply * w.getMaxSupplyWeight(), w.getMaxSupplyWeight(), maxSupply); maxSupply * w.getMaxSupplyWeight(), w.getMaxSupplyWeight(), maxSupply);
System.out.printf(" 销售优先级(负): %.2f (权重%.0f × %.2f)%n", writeLog(" 销售优先级(负): %.2f (权重%.0f × %.2f)",
salesPriority * w.getSalesDemandPriorityWeight(), salesPriority * w.getSalesDemandPriorityWeight(),
w.getSalesDemandPriorityWeight(), salesPriority); w.getSalesDemandPriorityWeight(), salesPriority);
} }
......
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 {
}
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