{"title":"钢铁生产系统中成本最小化和工作量平衡的多工序物流规划","authors":"Zhuohan Zhang, Ziyan Zhao, Yang Zhang, Shixin Liu","doi":"10.1109/ICNSC55942.2022.10004178","DOIUrl":null,"url":null,"abstract":"Logistics planning is a key to the coordination of multiple processes in steel production systems. This work investigates a new and practical bi-objective logistics planning problem arising from steelmaking-hot rolling-cold rolling processes. Its first objective is to minimize the sum of fixed costs, transportation costs, out-of-stock penalties, and inventory costs. The second one is to balance the workload of parallel machines. A mixed integer linear program is formulated for the concerned problem. To solve it, a genetic algorithm is problem-specifically designed. In it, the concerned bi-objective optimization problem is first transformed into a single-objective one by weighting two objective functions. Then, Pareto solutions are obtained through the presented algorithm by adjusting the weighted coefficients. Experimental results obtained by the presented algorithm are compared with those obtained by solving the mixed integer linear program with CPLEX. Its great performance is verified, thus showing its readiness to be applied in practice.","PeriodicalId":230499,"journal":{"name":"2022 IEEE International Conference on Networking, Sensing and Control (ICNSC)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multi-Process Logistics Planning for Cost Minimization and Workload Balance in Steel Production Systems\",\"authors\":\"Zhuohan Zhang, Ziyan Zhao, Yang Zhang, Shixin Liu\",\"doi\":\"10.1109/ICNSC55942.2022.10004178\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Logistics planning is a key to the coordination of multiple processes in steel production systems. This work investigates a new and practical bi-objective logistics planning problem arising from steelmaking-hot rolling-cold rolling processes. Its first objective is to minimize the sum of fixed costs, transportation costs, out-of-stock penalties, and inventory costs. The second one is to balance the workload of parallel machines. A mixed integer linear program is formulated for the concerned problem. To solve it, a genetic algorithm is problem-specifically designed. In it, the concerned bi-objective optimization problem is first transformed into a single-objective one by weighting two objective functions. Then, Pareto solutions are obtained through the presented algorithm by adjusting the weighted coefficients. Experimental results obtained by the presented algorithm are compared with those obtained by solving the mixed integer linear program with CPLEX. Its great performance is verified, thus showing its readiness to be applied in practice.\",\"PeriodicalId\":230499,\"journal\":{\"name\":\"2022 IEEE International Conference on Networking, Sensing and Control (ICNSC)\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE International Conference on Networking, Sensing and Control (ICNSC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICNSC55942.2022.10004178\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Conference on Networking, Sensing and Control (ICNSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNSC55942.2022.10004178","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multi-Process Logistics Planning for Cost Minimization and Workload Balance in Steel Production Systems
Logistics planning is a key to the coordination of multiple processes in steel production systems. This work investigates a new and practical bi-objective logistics planning problem arising from steelmaking-hot rolling-cold rolling processes. Its first objective is to minimize the sum of fixed costs, transportation costs, out-of-stock penalties, and inventory costs. The second one is to balance the workload of parallel machines. A mixed integer linear program is formulated for the concerned problem. To solve it, a genetic algorithm is problem-specifically designed. In it, the concerned bi-objective optimization problem is first transformed into a single-objective one by weighting two objective functions. Then, Pareto solutions are obtained through the presented algorithm by adjusting the weighted coefficients. Experimental results obtained by the presented algorithm are compared with those obtained by solving the mixed integer linear program with CPLEX. Its great performance is verified, thus showing its readiness to be applied in practice.