{"title":"Flow shop scheduling problem using hybrid quantum particle swarm optimization algorithm(HQPSO)","authors":"Qunxian Chen","doi":"10.1109/CINC.2010.5643845","DOIUrl":null,"url":null,"abstract":"The flow shop scheduling problem is a combinatorial optimization problem known to be NP-hard, which has captured the interest of a great number of researchers. Many different methods have been applied to solve FSSP and have obtained effective results, but these methods are not satisfying. Based on the quantum theory and particle swarm optimization ,this paper presents an HQPSO algorithm to solve FSSP. Experimental results show that the HQPSO algorithm for FSSP improves the search performance and shows the effectiveness of the algorithm to solve optimization problems..","PeriodicalId":227004,"journal":{"name":"2010 Second International Conference on Computational Intelligence and Natural Computing","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Second International Conference on Computational Intelligence and Natural Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CINC.2010.5643845","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
The flow shop scheduling problem is a combinatorial optimization problem known to be NP-hard, which has captured the interest of a great number of researchers. Many different methods have been applied to solve FSSP and have obtained effective results, but these methods are not satisfying. Based on the quantum theory and particle swarm optimization ,this paper presents an HQPSO algorithm to solve FSSP. Experimental results show that the HQPSO algorithm for FSSP improves the search performance and shows the effectiveness of the algorithm to solve optimization problems..
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