{"title":"热轧批规划多目标优化模型与算法","authors":"Shushi Ning, Wei Wang","doi":"10.1109/WCICA.2006.1714522","DOIUrl":null,"url":null,"abstract":"A multi-objective combinatorial optimization model is formulated for hot rolling lot planning problem in the production scheduling of iron and steel enterprises and a new modified multi-objective genetic local search algorithm is designed to solve the model. The model can solve the problem more precisely than previous methods. The algorithm can provide the schedulers with more than one solution in order to help schedulers make further decisions. Simulation experiment using production data shows that the model and algorithm are effective","PeriodicalId":375135,"journal":{"name":"2006 6th World Congress on Intelligent Control and Automation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Multi-objective Optimization Model and Algorithm for Hot Rolling Lot Planning\",\"authors\":\"Shushi Ning, Wei Wang\",\"doi\":\"10.1109/WCICA.2006.1714522\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A multi-objective combinatorial optimization model is formulated for hot rolling lot planning problem in the production scheduling of iron and steel enterprises and a new modified multi-objective genetic local search algorithm is designed to solve the model. The model can solve the problem more precisely than previous methods. The algorithm can provide the schedulers with more than one solution in order to help schedulers make further decisions. Simulation experiment using production data shows that the model and algorithm are effective\",\"PeriodicalId\":375135,\"journal\":{\"name\":\"2006 6th World Congress on Intelligent Control and Automation\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-10-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 6th World Congress on Intelligent Control and Automation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WCICA.2006.1714522\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 6th World Congress on Intelligent Control and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCICA.2006.1714522","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multi-objective Optimization Model and Algorithm for Hot Rolling Lot Planning
A multi-objective combinatorial optimization model is formulated for hot rolling lot planning problem in the production scheduling of iron and steel enterprises and a new modified multi-objective genetic local search algorithm is designed to solve the model. The model can solve the problem more precisely than previous methods. The algorithm can provide the schedulers with more than one solution in order to help schedulers make further decisions. Simulation experiment using production data shows that the model and algorithm are effective
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