Two-way mutation evolution strategies

Yong Liang, K. Leung
{"title":"Two-way mutation evolution strategies","authors":"Yong Liang, K. Leung","doi":"10.1109/CEC.2002.1007026","DOIUrl":null,"url":null,"abstract":"In this paper, a new two-way adaptive search mutation strategy is proposed, and a \"two-way evolution strategy\" (TWES) is established. The experimental results show that TWES yields much faster convergence than classical evolution strategies. This paper also discusses the relationship between the parameter setting and the convergent speed by TWES.","PeriodicalId":184547,"journal":{"name":"Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","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.2002.1007026","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 this paper, a new two-way adaptive search mutation strategy is proposed, and a "two-way evolution strategy" (TWES) is established. The experimental results show that TWES yields much faster convergence than classical evolution strategies. This paper also discusses the relationship between the parameter setting and the convergent speed by TWES.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
双向突变进化策略
本文提出了一种新的双向自适应搜索突变策略,建立了“双向进化策略”(TWES)。实验结果表明,该方法比经典进化策略收敛速度快得多。本文还讨论了参数设置与TWES收敛速度之间的关系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Development of FPGA based adaptive image enhancement filter system using genetic algorithms Intelligent predictive control of a power plant with evolutionary programming optimizer and neuro-fuzzy identifier Blocked stochastic sampling versus Estimation of Distribution Algorithms Distinguishing adaptive from non-adaptive evolution using Ashby's law of requisite variety An artificial immune network for multimodal function optimization
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1