{"title":"An improved CPSO algorithm","authors":"B. Borowska","doi":"10.1109/STC-CSIT.2016.7589854","DOIUrl":null,"url":null,"abstract":"This paper presents an improved particle swarm optimization algorithm (CPSO) in which corrective procedure was introduced. The aim of this corrective procedure is to set new, better velocities for some particles when their present velocities are inefficient. New velocities are the functions of previous and current velocities. The presented algorithm was tested with a set of benchmark functions and analyzed both in terms of their efficiency, premature convergence and the ability to avoid local optima. The results of the tests were compared with those obtained through the standard PSO and IPSO to demonstrate the superiority of CPSO.","PeriodicalId":433594,"journal":{"name":"2016 XIth International Scientific and Technical Conference Computer Sciences and Information Technologies (CSIT)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 XIth International Scientific and Technical Conference Computer Sciences and Information Technologies (CSIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/STC-CSIT.2016.7589854","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
This paper presents an improved particle swarm optimization algorithm (CPSO) in which corrective procedure was introduced. The aim of this corrective procedure is to set new, better velocities for some particles when their present velocities are inefficient. New velocities are the functions of previous and current velocities. The presented algorithm was tested with a set of benchmark functions and analyzed both in terms of their efficiency, premature convergence and the ability to avoid local optima. The results of the tests were compared with those obtained through the standard PSO and IPSO to demonstrate the superiority of CPSO.