{"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.