Hui Wang, Wenjun Wang, Hui Sun, Changhe Li, S. Rahnamayan, Yong Liu
{"title":"A modified cuckoo search algorithm for flow shop scheduling problem with blocking","authors":"Hui Wang, Wenjun Wang, Hui Sun, Changhe Li, S. Rahnamayan, Yong Liu","doi":"10.1109/CEC.2015.7256925","DOIUrl":null,"url":null,"abstract":"This paper presents a Modified Cuckoo Search (MCS) algorithm for solving flow shop scheduling problem with blocking to minimize the makespan. To handle the discrete variables of the job scheduling problem, the smallest position value (SPV) rule is used to convert continuous solutions into discrete job permutations. The Nawaz-Enscore-Ham (NEH) heuristic method is utilized for generating high quality initial solutions. Moreover, two frequently used swap and insert operators are employed for enhancing the local search. To verify the performance of the proposed MCS algorithm, experiments are conducted on Taillard's benchmark set. Results show that MCS performs better than the standard CS and some previous algorithms proposed in the literature.","PeriodicalId":403666,"journal":{"name":"2015 IEEE Congress on Evolutionary Computation (CEC)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE Congress on Evolutionary Computation (CEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CEC.2015.7256925","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
This paper presents a Modified Cuckoo Search (MCS) algorithm for solving flow shop scheduling problem with blocking to minimize the makespan. To handle the discrete variables of the job scheduling problem, the smallest position value (SPV) rule is used to convert continuous solutions into discrete job permutations. The Nawaz-Enscore-Ham (NEH) heuristic method is utilized for generating high quality initial solutions. Moreover, two frequently used swap and insert operators are employed for enhancing the local search. To verify the performance of the proposed MCS algorithm, experiments are conducted on Taillard's benchmark set. Results show that MCS performs better than the standard CS and some previous algorithms proposed in the literature.