Kai Zhang, Feng Cai, Aiguo Shi, Bo Zhou, Yongsheng Zhang
{"title":"Nonlinear optimal selection based on niche evolution algorithm","authors":"Kai Zhang, Feng Cai, Aiguo Shi, Bo Zhou, Yongsheng Zhang","doi":"10.1109/WCICA.2004.1341984","DOIUrl":null,"url":null,"abstract":"In multidimensional nonlinear optimal selection, Genetic Algorithm is often unable to get all global solutions, and needs a long time to solve problems with continuous variables. So a nonlinear optimal selection model based on multidimensional niche evolution algorithm (NEA) was proposed, and its parameters selection principal was also discussed. Computer simulations successfully demonstrates that this model has virtue of speediness high efficiency and good robustness, and it can successfully find out all those global optimal results in complicated nonlinear optimal selection.","PeriodicalId":331407,"journal":{"name":"Fifth World Congress on Intelligent Control and Automation (IEEE Cat. No.04EX788)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Fifth World Congress on Intelligent Control and Automation (IEEE Cat. No.04EX788)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCICA.2004.1341984","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
In multidimensional nonlinear optimal selection, Genetic Algorithm is often unable to get all global solutions, and needs a long time to solve problems with continuous variables. So a nonlinear optimal selection model based on multidimensional niche evolution algorithm (NEA) was proposed, and its parameters selection principal was also discussed. Computer simulations successfully demonstrates that this model has virtue of speediness high efficiency and good robustness, and it can successfully find out all those global optimal results in complicated nonlinear optimal selection.