A Survey on Meta-heuristic Algorithms for Global Optimization Problems

A. H. Zaied, Mahmoud Ismail, S. El-Sayed
{"title":"A Survey on Meta-heuristic Algorithms for Global Optimization Problems","authors":"A. H. Zaied, Mahmoud Ismail, S. El-Sayed","doi":"10.54216/jisiot.010104","DOIUrl":null,"url":null,"abstract":"Optimization is a more important field of research. With increasing the complexity of real-world problems, the more efficient and reliable optimization algorithms vital. Traditional methods are unable to solve these problems so, the first choice for solving these problems becomes meta-heuristic algorithms. Meta-heuristic algorithms proved their ability to solve more complex problems and giving more satisfying results. In this paper, we introduce the more popular meta-heuristic algorithms and their applications in addition to providing the more recent references for these algorithms.","PeriodicalId":122556,"journal":{"name":"Journal of Intelligent Systems and Internet of Things","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Intelligent Systems and Internet of Things","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.54216/jisiot.010104","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12

Abstract

Optimization is a more important field of research. With increasing the complexity of real-world problems, the more efficient and reliable optimization algorithms vital. Traditional methods are unable to solve these problems so, the first choice for solving these problems becomes meta-heuristic algorithms. Meta-heuristic algorithms proved their ability to solve more complex problems and giving more satisfying results. In this paper, we introduce the more popular meta-heuristic algorithms and their applications in addition to providing the more recent references for these algorithms.
全局优化问题的元启发式算法综述
优化是一个更重要的研究领域。随着现实世界问题的日益复杂,更加高效可靠的优化算法至关重要。传统的方法无法解决这些问题,因此,解决这些问题的首选方法是元启发式算法。元启发式算法证明了其解决更复杂问题的能力,并给出了更令人满意的结果。在本文中,我们介绍了较流行的元启发式算法及其应用,并提供了这些算法的最新参考。
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
CiteScore
1.70
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:604180095
Book学术官方微信