{"title":"在不相同作业规模的单机问题中最小化总加权延迟","authors":"M. Bijari, Omid Rajabi","doi":"10.1109/IEOM.2015.7093753","DOIUrl":null,"url":null,"abstract":"In this paper, minimizing total weighted tardiness in single machine problem has been considered. Jobs have different size, also batch processing assumption is considered. We developed a new Mixed Integer Linear Programming (MILP) to the problem. The model solves the problem faster than previous model; due to the proposed model restricted the solution space. Some instances problems are generated in order to evaluate the proposed model. Comparing the solution time of the proposed model with the old model shows the efficiency of the new model. Computational result is shown that the proposed model decrease CPU time at more than 90% instances. In some instance CPU time decreased about 70%.","PeriodicalId":410110,"journal":{"name":"2015 International Conference on Industrial Engineering and Operations Management (IEOM)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Minimizing total weighted tardiness in single machine problem with non-identical job sizes\",\"authors\":\"M. Bijari, Omid Rajabi\",\"doi\":\"10.1109/IEOM.2015.7093753\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, minimizing total weighted tardiness in single machine problem has been considered. Jobs have different size, also batch processing assumption is considered. We developed a new Mixed Integer Linear Programming (MILP) to the problem. The model solves the problem faster than previous model; due to the proposed model restricted the solution space. Some instances problems are generated in order to evaluate the proposed model. Comparing the solution time of the proposed model with the old model shows the efficiency of the new model. Computational result is shown that the proposed model decrease CPU time at more than 90% instances. In some instance CPU time decreased about 70%.\",\"PeriodicalId\":410110,\"journal\":{\"name\":\"2015 International Conference on Industrial Engineering and Operations Management (IEOM)\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-03-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Conference on Industrial Engineering and Operations Management (IEOM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IEOM.2015.7093753\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Industrial Engineering and Operations Management (IEOM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEOM.2015.7093753","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Minimizing total weighted tardiness in single machine problem with non-identical job sizes
In this paper, minimizing total weighted tardiness in single machine problem has been considered. Jobs have different size, also batch processing assumption is considered. We developed a new Mixed Integer Linear Programming (MILP) to the problem. The model solves the problem faster than previous model; due to the proposed model restricted the solution space. Some instances problems are generated in order to evaluate the proposed model. Comparing the solution time of the proposed model with the old model shows the efficiency of the new model. Computational result is shown that the proposed model decrease CPU time at more than 90% instances. In some instance CPU time decreased about 70%.