基于小生境算法的改进免疫遗传算法及其应用

Lili Dong, C. Xue, Guohua Li
{"title":"基于小生境算法的改进免疫遗传算法及其应用","authors":"Lili Dong, C. Xue, Guohua Li","doi":"10.1109/IEEC.2010.5533280","DOIUrl":null,"url":null,"abstract":"In order to overcome traditional genetic algorithm (GA)'s deficiency of slow convergence, and Niche algorithm's too fast convergence, this paper presents a new Improved Immune Genetic Algorithm (IIGA) based on the improved Niche algorithm. Firstly, the improved Niche algorithm, including convergence function, and \"noise\" chromosome, is given. Then based on the proposed flowchart of IIGA, the steps of the algorithm are introduced in detail. Finally, the IIGA is exemplified, and proved to be feasible and effective by comparing with self-adaptive Genetic Algorithm(SAGA) and traditional GA.","PeriodicalId":307678,"journal":{"name":"2010 2nd International Symposium on Information Engineering and Electronic Commerce","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An Improved Immune Genetic Algorithm Based on Niche Algorithm and Its Application\",\"authors\":\"Lili Dong, C. Xue, Guohua Li\",\"doi\":\"10.1109/IEEC.2010.5533280\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to overcome traditional genetic algorithm (GA)'s deficiency of slow convergence, and Niche algorithm's too fast convergence, this paper presents a new Improved Immune Genetic Algorithm (IIGA) based on the improved Niche algorithm. Firstly, the improved Niche algorithm, including convergence function, and \\\"noise\\\" chromosome, is given. Then based on the proposed flowchart of IIGA, the steps of the algorithm are introduced in detail. Finally, the IIGA is exemplified, and proved to be feasible and effective by comparing with self-adaptive Genetic Algorithm(SAGA) and traditional GA.\",\"PeriodicalId\":307678,\"journal\":{\"name\":\"2010 2nd International Symposium on Information Engineering and Electronic Commerce\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-07-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 2nd International Symposium on Information Engineering and Electronic Commerce\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IEEC.2010.5533280\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 2nd International Symposium on Information Engineering and Electronic Commerce","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEEC.2010.5533280","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

为了克服传统遗传算法收敛速度慢和小生境算法收敛速度过快的缺点,在改进小生境算法的基础上提出了一种新的改进免疫遗传算法。首先,给出了改进的小生境算法,包括收敛函数和“噪声”染色体。然后根据提出的IIGA流程图,详细介绍了算法的步骤。最后,通过与自适应遗传算法(SAGA)和传统遗传算法的比较,验证了该算法的可行性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Improved Immune Genetic Algorithm Based on Niche Algorithm and Its Application
In order to overcome traditional genetic algorithm (GA)'s deficiency of slow convergence, and Niche algorithm's too fast convergence, this paper presents a new Improved Immune Genetic Algorithm (IIGA) based on the improved Niche algorithm. Firstly, the improved Niche algorithm, including convergence function, and "noise" chromosome, is given. Then based on the proposed flowchart of IIGA, the steps of the algorithm are introduced in detail. Finally, the IIGA is exemplified, and proved to be feasible and effective by comparing with self-adaptive Genetic Algorithm(SAGA) and traditional GA.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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