{"title":"A new version of Gravitational Search Algorithm with negative mass","authors":"Fatemeh Khajooei, E. Rashedi","doi":"10.1109/CSIEC.2016.7482123","DOIUrl":null,"url":null,"abstract":"The Gravitational Search Algorithm (GSA) is a stochastic population-based meta-heuristic algorithm that is based on gravity and mass interactions. In this paper, using the concept of antigravity, a new version of GSA is introduced that has both positive and negative masses. Therefore it has both gravity force and antigravity forces. The proposed algorithm improves the ability of GSA to further explore the search space. The proposed algorithm is tested on the several benchmark functions and compared with the standard GSA. The obtained results confirm the efficiency of the proposed method.","PeriodicalId":268101,"journal":{"name":"2016 1st Conference on Swarm Intelligence and Evolutionary Computation (CSIEC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 1st Conference on Swarm Intelligence and Evolutionary Computation (CSIEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSIEC.2016.7482123","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13
Abstract
The Gravitational Search Algorithm (GSA) is a stochastic population-based meta-heuristic algorithm that is based on gravity and mass interactions. In this paper, using the concept of antigravity, a new version of GSA is introduced that has both positive and negative masses. Therefore it has both gravity force and antigravity forces. The proposed algorithm improves the ability of GSA to further explore the search space. The proposed algorithm is tested on the several benchmark functions and compared with the standard GSA. The obtained results confirm the efficiency of the proposed method.