{"title":"Design of parallel distributed algorithm for the Permutation Flow Shop Problem","authors":"Samia Kouki, M. Jemni, T. Ladhari","doi":"10.1109/NOTERE.2010.5536815","DOIUrl":null,"url":null,"abstract":"This paper deals with the resolution of the Permutation Flow Shop Problem (PFSP) which requires scheduling n jobs through m machines that are placed in series so as to minimize the makespan. In this study, we focus on parallel methods for solving the one-machine PFSP. We present a parallel distributed Algorithm for this problem with extensive computational results on cluster of computers using well-known benchmarks. The experimental evaluation of our distributed parallel algorithm gives promising results and shows clearly the benefit of the parallel paradigm to solve large-scale instances in moderate CPU time.","PeriodicalId":431237,"journal":{"name":"2010 10th Annual International Conference on New Technologies of Distributed Systems (NOTERE)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 10th Annual International Conference on New Technologies of Distributed Systems (NOTERE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NOTERE.2010.5536815","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
This paper deals with the resolution of the Permutation Flow Shop Problem (PFSP) which requires scheduling n jobs through m machines that are placed in series so as to minimize the makespan. In this study, we focus on parallel methods for solving the one-machine PFSP. We present a parallel distributed Algorithm for this problem with extensive computational results on cluster of computers using well-known benchmarks. The experimental evaluation of our distributed parallel algorithm gives promising results and shows clearly the benefit of the parallel paradigm to solve large-scale instances in moderate CPU time.