{"title":"Asynchronous self-adjustable island genetic algorithm for multi-objective optimization problems","authors":"Zhong-Yao Zhu, K. Leung","doi":"10.1109/CEC.2002.1007034","DOIUrl":null,"url":null,"abstract":"In this paper, we present a new algorithm-asynchronous self-adjustable island genetic algorithm (aSAIGA) for multi-objective optimization problems. The proposed algorithm is built upon the coarse-grained architecture, which is divided into sub-processes and distributed amongst several island processors. In each sub-process, an asynchronous communication operation and a self-adjusting operation are adopted to enhance the algorithm in both speedup and global searching capabilities. Satisfactory results and significant speedup can be achieved by aSAIGA, as shown by simulation.","PeriodicalId":184547,"journal":{"name":"Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CEC.2002.1007034","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 21
Abstract
In this paper, we present a new algorithm-asynchronous self-adjustable island genetic algorithm (aSAIGA) for multi-objective optimization problems. The proposed algorithm is built upon the coarse-grained architecture, which is divided into sub-processes and distributed amongst several island processors. In each sub-process, an asynchronous communication operation and a self-adjusting operation are adopted to enhance the algorithm in both speedup and global searching capabilities. Satisfactory results and significant speedup can be achieved by aSAIGA, as shown by simulation.
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