{"title":"Improved Differential Evolution for Function Optimization","authors":"Zhigang Zhou","doi":"10.1109/MVHI.2010.146","DOIUrl":null,"url":null,"abstract":"This paper presents an improved differential evolution (DE) algorithm to enhance the performance of DE. The proposed approach is called MPTDE which employs a novel mutation operator. The main idea of MPTDE is to conduct a mutation on each individual and select a fitter one between the current one and the mutated one as the new current individual. In order to verify the performance of MPTDE, we test it on ten well-known benchmark functions. The experimental results show that MPTDE outperforms DE on majority of test functions.","PeriodicalId":34860,"journal":{"name":"HumanMachine Communication Journal","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2010-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"HumanMachine Communication Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MVHI.2010.146","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Social Sciences","Score":null,"Total":0}
引用次数: 0
Abstract
This paper presents an improved differential evolution (DE) algorithm to enhance the performance of DE. The proposed approach is called MPTDE which employs a novel mutation operator. The main idea of MPTDE is to conduct a mutation on each individual and select a fitter one between the current one and the mutated one as the new current individual. In order to verify the performance of MPTDE, we test it on ten well-known benchmark functions. The experimental results show that MPTDE outperforms DE on majority of test functions.