遗传算法参数对结构优化设计搜索的影响

Z. E. Maskaoui, S. Jalal, L. Bousshine
{"title":"遗传算法参数对结构优化设计搜索的影响","authors":"Z. E. Maskaoui, S. Jalal, L. Bousshine","doi":"10.9790/1684-140305124130","DOIUrl":null,"url":null,"abstract":"This paper investigates the effects of genetic algorithm parameters on the performance of optimum structural search. The most significant of these parameters can be grouped according to their biologicallyinspired functions: population size, initial population, and crossover and mutation operators. However, since the genetic algorithms use a random search the numerical results presented in this paper show the extent to which the quality of solution depends on the choice of these parameters.","PeriodicalId":14565,"journal":{"name":"IOSR Journal of Mechanical and Civil Engineering","volume":"4 1","pages":"124-130"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Genetic Algorithm Parameters Effect on the Optimal Structural Design Search\",\"authors\":\"Z. E. Maskaoui, S. Jalal, L. Bousshine\",\"doi\":\"10.9790/1684-140305124130\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper investigates the effects of genetic algorithm parameters on the performance of optimum structural search. The most significant of these parameters can be grouped according to their biologicallyinspired functions: population size, initial population, and crossover and mutation operators. However, since the genetic algorithms use a random search the numerical results presented in this paper show the extent to which the quality of solution depends on the choice of these parameters.\",\"PeriodicalId\":14565,\"journal\":{\"name\":\"IOSR Journal of Mechanical and Civil Engineering\",\"volume\":\"4 1\",\"pages\":\"124-130\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IOSR Journal of Mechanical and Civil Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.9790/1684-140305124130\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IOSR Journal of Mechanical and Civil Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.9790/1684-140305124130","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

摘要

研究了遗传算法参数对最优结构搜索性能的影响。这些参数中最重要的参数可以根据它们的生物学启发函数进行分组:种群大小、初始种群、交叉和突变算子。然而,由于遗传算法使用随机搜索,本文给出的数值结果显示了解的质量取决于这些参数的选择的程度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Genetic Algorithm Parameters Effect on the Optimal Structural Design Search
This paper investigates the effects of genetic algorithm parameters on the performance of optimum structural search. The most significant of these parameters can be grouped according to their biologicallyinspired functions: population size, initial population, and crossover and mutation operators. However, since the genetic algorithms use a random search the numerical results presented in this paper show the extent to which the quality of solution depends on the choice of these parameters.
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