Hu Songwei, He Lifang, Si Xu, Zhang Yuanyuan, Hao Pengyu
{"title":"An Effective Krill Herd Algorithm for Numerical Optimization","authors":"Hu Songwei, He Lifang, Si Xu, Zhang Yuanyuan, Hao Pengyu","doi":"10.14257/IJHIT.2016.9.7.13","DOIUrl":null,"url":null,"abstract":"The krill herd (KH) algorithm is a novel swarm intelligent algorithm which is inspired the herding behavior of the krill swarms. The various test results in the relevant literature show that the KH algorithm has better performance than the other swarm intelligent algorithm for optimization problem. In order to further improve the performance of the KH algorithm, an improved KH is proposed in this paper. The algorithm is performed on ten test functions and the results are compared with the basic KH algorithm, PSO, DE and GA algorithm. The experimental results indicate that the improved algorithm is a good method for numerical optimization problem.","PeriodicalId":170772,"journal":{"name":"International Journal of Hybrid Information Technology","volume":"260 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Hybrid Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14257/IJHIT.2016.9.7.13","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
The krill herd (KH) algorithm is a novel swarm intelligent algorithm which is inspired the herding behavior of the krill swarms. The various test results in the relevant literature show that the KH algorithm has better performance than the other swarm intelligent algorithm for optimization problem. In order to further improve the performance of the KH algorithm, an improved KH is proposed in this paper. The algorithm is performed on ten test functions and the results are compared with the basic KH algorithm, PSO, DE and GA algorithm. The experimental results indicate that the improved algorithm is a good method for numerical optimization problem.