{"title":"A Fast Opposition-Based Differential Evolution with Cauchy Mutation","authors":"Yong Wu, Bin Zhao, Jinglei Guo","doi":"10.1109/GCIS.2012.91","DOIUrl":null,"url":null,"abstract":"Opposition-based Differential Evolution (ODE) has been proved to be an effective method to Differential Evolution (DE) in solving many optimization functions, and it's faster and more robust convergence than classical DE. In this paper, a fast ODE algorithm (FODE), using a local search method with Cauchy mutation is proposed. The simulation experiments are conducted on a comprehensive set of 10 complex benchmark functions. Compared with ODE, FODE is faster and more robust.","PeriodicalId":337629,"journal":{"name":"2012 Third Global Congress on Intelligent Systems","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Third Global Congress on Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GCIS.2012.91","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
Opposition-based Differential Evolution (ODE) has been proved to be an effective method to Differential Evolution (DE) in solving many optimization functions, and it's faster and more robust convergence than classical DE. In this paper, a fast ODE algorithm (FODE), using a local search method with Cauchy mutation is proposed. The simulation experiments are conducted on a comprehensive set of 10 complex benchmark functions. Compared with ODE, FODE is faster and more robust.