Tsung-Ying Chiang, Ting-Cheng Feng, Tzuu-Hseng S. Li
{"title":"Two-Step gravitational search algorithm","authors":"Tsung-Ying Chiang, Ting-Cheng Feng, Tzuu-Hseng S. Li","doi":"10.1109/ICCSS.2015.7281156","DOIUrl":null,"url":null,"abstract":"In this paper, we present an efficient algorithm for solving optimization problems, which is based on gravitational search algorithm (GSA). In the proposed technique, called Two-Step method, the best solution of position will be considered and calculated with another agents, and the fitness of extended agents are compared with agents in original gravitation field, which can reinforce the exploration and exploitation performance. Ten benchmark functions are used to evaluate and to compare performance of the presented algorithm with GSA based on the same function evaluations. The initialized populations are produced randomly and are identical for each round of all the algorithms in the same benchmark function. The obtained results confirm the better performance of the proposed method in solving various nonlinear functions.","PeriodicalId":299619,"journal":{"name":"2015 International Conference on Informative and Cybernetics for Computational Social Systems (ICCSS)","volume":"159 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Informative and Cybernetics for Computational Social Systems (ICCSS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSS.2015.7281156","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In this paper, we present an efficient algorithm for solving optimization problems, which is based on gravitational search algorithm (GSA). In the proposed technique, called Two-Step method, the best solution of position will be considered and calculated with another agents, and the fitness of extended agents are compared with agents in original gravitation field, which can reinforce the exploration and exploitation performance. Ten benchmark functions are used to evaluate and to compare performance of the presented algorithm with GSA based on the same function evaluations. The initialized populations are produced randomly and are identical for each round of all the algorithms in the same benchmark function. The obtained results confirm the better performance of the proposed method in solving various nonlinear functions.