On the Analysis of Performance of the Artificial Tribe Algorithm

Tanggong Chen, Xiaowei Wei, Wenhui Jia, Zhi Liu
{"title":"On the Analysis of Performance of the Artificial Tribe Algorithm","authors":"Tanggong Chen, Xiaowei Wei, Wenhui Jia, Zhi Liu","doi":"10.1109/CSO.2010.112","DOIUrl":null,"url":null,"abstract":"Artificial Tribe Algorithm (ATA) is a novel intelligent optimization algorithm based on the simulation of bionic intelligent optimization algorithm. This work discusses the main factors which influence the performance of ATA, and compares the performance of ATA with that of genetic algorithm (GA), particle swarm optimization (PSO), and artificial fish-swarm algorithm (AFSA) for optimization multivariable functions. The simulation results showed that ATA outperforms the mentioned algorithms in global optimization problems.","PeriodicalId":427481,"journal":{"name":"2010 Third International Joint Conference on Computational Science and Optimization","volume":"66 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Third International Joint Conference on Computational Science and Optimization","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSO.2010.112","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

Artificial Tribe Algorithm (ATA) is a novel intelligent optimization algorithm based on the simulation of bionic intelligent optimization algorithm. This work discusses the main factors which influence the performance of ATA, and compares the performance of ATA with that of genetic algorithm (GA), particle swarm optimization (PSO), and artificial fish-swarm algorithm (AFSA) for optimization multivariable functions. The simulation results showed that ATA outperforms the mentioned algorithms in global optimization problems.
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
人工部落算法的性能分析
人工部落算法(ATA)是在模拟仿生智能优化算法的基础上提出的一种新型智能优化算法。本文讨论了影响多变量函数优化性能的主要因素,并将多变量函数优化性能与遗传算法(GA)、粒子群算法(PSO)和人工鱼群算法(AFSA)进行了比较。仿真结果表明,该算法在全局优化问题上优于上述算法。
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
Assessing the Internal Fraud Risk of Chinese Commercial Banks A Fast Bidirectional Method for Mining Maximal Frequent Itemsets A Prediction of the Monthly Precipitation Model Based on PSO-ANN and its Applications On the Analysis of Performance of the Artificial Tribe Algorithm Analysis on the Volatility of SHIBOR
×
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:481959085
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