{"title":"Modified Differential Evolution for Dynamic Optimization Problems","authors":"Jiang Liqiang, Qiang Hongfu","doi":"10.1109/ISDEA.2012.647","DOIUrl":null,"url":null,"abstract":"Modified differential evolution algorithm (MDE) is proposed for dynamic optimization problems. The new algorithm divides the population into two, a main subpopulation and an assistant one. The main subpopulation keeps invariant and searches locally. The assistant subpopulatioin is re-initialized at random and searches globally. The results show that MDE can track the changing extreme promptly and accurately and is capable of efficiently solving dynamic optmization problems.","PeriodicalId":267532,"journal":{"name":"2012 Second International Conference on Intelligent System Design and Engineering Application","volume":"285 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Second International Conference on Intelligent System Design and Engineering Application","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISDEA.2012.647","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
Modified differential evolution algorithm (MDE) is proposed for dynamic optimization problems. The new algorithm divides the population into two, a main subpopulation and an assistant one. The main subpopulation keeps invariant and searches locally. The assistant subpopulatioin is re-initialized at random and searches globally. The results show that MDE can track the changing extreme promptly and accurately and is capable of efficiently solving dynamic optmization problems.
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