On optimal population size of genetic algorithms

J. Alander
{"title":"On optimal population size of genetic algorithms","authors":"J. Alander","doi":"10.1109/CMPEUR.1992.218485","DOIUrl":null,"url":null,"abstract":"A description is given of the results of experiments to find the optimum population size for genetic algorithms as a function of problem complexity. It seems that for moderate problem complexity the optimal population size for problems coded as bitstrings is approximately the length of the string in bits for sequential machines. This result is also consistent with earlier experimentation. In parallel architectures the optimal population size is larger than in the corresponding sequential cases, but the exact figures seem to be sensitive to implementation details.<<ETX>>","PeriodicalId":390273,"journal":{"name":"CompEuro 1992 Proceedings Computer Systems and Software Engineering","volume":"148 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"247","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"CompEuro 1992 Proceedings Computer Systems and Software Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CMPEUR.1992.218485","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 247

Abstract

A description is given of the results of experiments to find the optimum population size for genetic algorithms as a function of problem complexity. It seems that for moderate problem complexity the optimal population size for problems coded as bitstrings is approximately the length of the string in bits for sequential machines. This result is also consistent with earlier experimentation. In parallel architectures the optimal population size is larger than in the corresponding sequential cases, but the exact figures seem to be sensitive to implementation details.<>
遗传算法的最优种群大小
描述了遗传算法的最佳种群大小随问题复杂性的函数的实验结果。对于中等复杂性的问题,用位串编码的问题的最佳总体大小似乎近似于序列机器的字符串长度。这一结果也与早期的实验结果一致。在并行体系结构中,最优的人口规模比相应的顺序情况下更大,但确切的数字似乎对实现细节很敏感。
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