Guangzhen Cui, Ling Li, X. Lv, Xiaodong Sun, Huaixiao Wang
{"title":"A New Quantum Mutation Operation and Dynamic Population Technology for Job Shop Scheduling Problem","authors":"Guangzhen Cui, Ling Li, X. Lv, Xiaodong Sun, Huaixiao Wang","doi":"10.1109/ICISCAE.2018.8666861","DOIUrl":null,"url":null,"abstract":"In this paper, an improvement method of quantum genetic algorithm (QGA) is proposed on the basis of the principle to solve the job shop scheduling problem. A new quantum mutation operation is put forward to generate individual of next generation according to the guide chromosome, and dynamic population technology is adopted to adjust the population scale of QGA. Finally, the simulation examples are applied to verify the effectiveness and superiority of the improved quantum genetic algorithm and the rationality of the encoding method.","PeriodicalId":129861,"journal":{"name":"2018 International Conference on Information Systems and Computer Aided Education (ICISCAE)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Information Systems and Computer Aided Education (ICISCAE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICISCAE.2018.8666861","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, an improvement method of quantum genetic algorithm (QGA) is proposed on the basis of the principle to solve the job shop scheduling problem. A new quantum mutation operation is put forward to generate individual of next generation according to the guide chromosome, and dynamic population technology is adopted to adjust the population scale of QGA. Finally, the simulation examples are applied to verify the effectiveness and superiority of the improved quantum genetic algorithm and the rationality of the encoding method.