Performance analysis of the Imperialist Competitive algorithm using benchmark functions

M. A. F. Mollinetti, J. Almeida, Rodrigo Lisbôa Pereira, O. N. Teixeira
{"title":"Performance analysis of the Imperialist Competitive algorithm using benchmark functions","authors":"M. A. F. Mollinetti, J. Almeida, Rodrigo Lisbôa Pereira, O. N. Teixeira","doi":"10.1109/SOCPAR.2013.7054157","DOIUrl":null,"url":null,"abstract":"In this paper, in order to prove the effectiveness of the Imperialist Competitive Algorithm - a socio-political inspired algorithm-on finding the optimal solution for different kinds of minimization functions as well as different kinds of landscapes. The reliability and quality of solutions for mathematical minimization functions of the ICA is evaluated by seven distinct benchmark functions where each one displays different behaviors, and then the results of each test is compared with two other optimization techniques, the Particle Swarm Optimization (PSO) and the Differential Evolution (DE).","PeriodicalId":315126,"journal":{"name":"2013 International Conference on Soft Computing and Pattern Recognition (SoCPaR)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Conference on Soft Computing and Pattern Recognition (SoCPaR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SOCPAR.2013.7054157","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, in order to prove the effectiveness of the Imperialist Competitive Algorithm - a socio-political inspired algorithm-on finding the optimal solution for different kinds of minimization functions as well as different kinds of landscapes. The reliability and quality of solutions for mathematical minimization functions of the ICA is evaluated by seven distinct benchmark functions where each one displays different behaviors, and then the results of each test is compared with two other optimization techniques, the Particle Swarm Optimization (PSO) and the Differential Evolution (DE).
使用基准函数的帝国竞争算法的性能分析
在本文中,为了证明帝国主义竞争算法-一种社会政治启发算法-在寻找不同类型的最小化函数和不同类型的景观的最优解方面的有效性。通过7个不同的基准函数来评估ICA数学最小函数解的可靠性和质量,每个基准函数表现出不同的行为,然后将每个测试的结果与另外两种优化技术,粒子群优化(PSO)和差分进化(DE)进行比较。
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 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信