{"title":"具有精确时滞的置换流水车间调度问题的边界,以使总早迟到最小化","authors":"Imen Hamdi","doi":"10.1504/IJOR.2017.080596","DOIUrl":null,"url":null,"abstract":"In this paper, we investigate the problem of n-jobs scheduling in an m-machine permutation flowshop with exact time lags between consecutive operations of each job. The exact time lag is defined as the time elapsed between every couple of successive operations of the same job which is equal to a prescribed value. The aim is to find a feasible schedule that minimises the total tardiness and earliness. We propose three mathematical formulations, which are then solved by running the commercial software CPLEX to provide an optimal solution for small size problems. As the problem is shown to be strongly NP-hard, we propose new improved upper and lower bounds useful for large size problems. We then evaluate their effectiveness through an extensive computational experiment.","PeriodicalId":42388,"journal":{"name":"International Journal of Combinatorial Optimization Problems and Informatics","volume":null,"pages":null},"PeriodicalIF":0.3000,"publicationDate":"2014-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Bounds for the permutation flowshop scheduling problem with exact time lags to minimize the total earliness and tardiness\",\"authors\":\"Imen Hamdi\",\"doi\":\"10.1504/IJOR.2017.080596\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we investigate the problem of n-jobs scheduling in an m-machine permutation flowshop with exact time lags between consecutive operations of each job. The exact time lag is defined as the time elapsed between every couple of successive operations of the same job which is equal to a prescribed value. The aim is to find a feasible schedule that minimises the total tardiness and earliness. We propose three mathematical formulations, which are then solved by running the commercial software CPLEX to provide an optimal solution for small size problems. As the problem is shown to be strongly NP-hard, we propose new improved upper and lower bounds useful for large size problems. We then evaluate their effectiveness through an extensive computational experiment.\",\"PeriodicalId\":42388,\"journal\":{\"name\":\"International Journal of Combinatorial Optimization Problems and Informatics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.3000,\"publicationDate\":\"2014-12-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Combinatorial Optimization Problems and Informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/IJOR.2017.080596\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"MATHEMATICS, APPLIED\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Combinatorial Optimization Problems and Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJOR.2017.080596","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
Bounds for the permutation flowshop scheduling problem with exact time lags to minimize the total earliness and tardiness
In this paper, we investigate the problem of n-jobs scheduling in an m-machine permutation flowshop with exact time lags between consecutive operations of each job. The exact time lag is defined as the time elapsed between every couple of successive operations of the same job which is equal to a prescribed value. The aim is to find a feasible schedule that minimises the total tardiness and earliness. We propose three mathematical formulations, which are then solved by running the commercial software CPLEX to provide an optimal solution for small size problems. As the problem is shown to be strongly NP-hard, we propose new improved upper and lower bounds useful for large size problems. We then evaluate their effectiveness through an extensive computational experiment.