A Nature Inspired Heuristic Optimization Algorithm Based on Lightning

H. Shareef, M. Islam, A. A. Ibrahim, A. H. Mutlag
{"title":"A Nature Inspired Heuristic Optimization Algorithm Based on Lightning","authors":"H. Shareef, M. Islam, A. A. Ibrahim, A. H. Mutlag","doi":"10.1109/AIMS.2015.12","DOIUrl":null,"url":null,"abstract":"This paper presents a nature inspired heuristic optimization algorithm based on lightning process called the lightning search algorithm (LSA) to solve optimization problems. It is derived from the natural phenomenon of lightning and the process of step leader propagation using the theory of fast particles. Three particle types are established to characterize the transition particles that generate the first step leader population, the space particles that try to become the leader, and the lead particle that represent the particle excited from best positioned step leader. To access the correctness and efficiency of the suggested algorithm, the LSA is verified using a well-used 10 benchmark functions with several characteristics. A comparative study with two other established methods is conducted to confirm and compare the performance of the LSA. The result exhibits that the LSA usually delivers better results compared with the other experimented methods with a high convergence rate.","PeriodicalId":121874,"journal":{"name":"2015 3rd International Conference on Artificial Intelligence, Modelling and Simulation (AIMS)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 3rd International Conference on Artificial Intelligence, Modelling and Simulation (AIMS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AIMS.2015.12","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

Abstract

This paper presents a nature inspired heuristic optimization algorithm based on lightning process called the lightning search algorithm (LSA) to solve optimization problems. It is derived from the natural phenomenon of lightning and the process of step leader propagation using the theory of fast particles. Three particle types are established to characterize the transition particles that generate the first step leader population, the space particles that try to become the leader, and the lead particle that represent the particle excited from best positioned step leader. To access the correctness and efficiency of the suggested algorithm, the LSA is verified using a well-used 10 benchmark functions with several characteristics. A comparative study with two other established methods is conducted to confirm and compare the performance of the LSA. The result exhibits that the LSA usually delivers better results compared with the other experimented methods with a high convergence rate.
基于闪电的自然启发启发式优化算法
提出了一种基于闪电过程的自然启发式优化算法——闪电搜索算法(LSA)来解决优化问题。它是利用快粒子理论推导出闪电的自然现象和阶跃引线传播过程。建立了三种粒子类型来描述产生第一步领导者群体的过渡粒子、试图成为领导者的空间粒子和代表从最佳位置的步骤领导者激发的粒子的先导粒子。为了验证建议算法的正确性和效率,使用具有几个特征的10个常用基准函数来验证LSA。并与其他两种已建立的方法进行了对比研究,以确认和比较LSA的性能。结果表明,与其他实验方法相比,LSA通常具有更好的结果,具有较高的收敛速度。
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