{"title":"Memetic-CLA-PSO: A Hybrid Model for Optimization","authors":"Mojdeh Akhtari, M. Meybodi","doi":"10.1109/UKSIM.2011.14","DOIUrl":null,"url":null,"abstract":"In this paper a hybrid model which is a combination of Memetic algorithm, cellular learning automata (CLA) and PSO is proposed. The proposed algorithm in addition to maintaining diversity; largely reduces the probability of getting trap in local optima. Experimental results on eight optimization problems show the superiority of the proposed algorithm.","PeriodicalId":161995,"journal":{"name":"2011 UkSim 13th International Conference on Computer Modelling and Simulation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 UkSim 13th International Conference on Computer Modelling and Simulation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/UKSIM.2011.14","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
In this paper a hybrid model which is a combination of Memetic algorithm, cellular learning automata (CLA) and PSO is proposed. The proposed algorithm in addition to maintaining diversity; largely reduces the probability of getting trap in local optima. Experimental results on eight optimization problems show the superiority of the proposed algorithm.