{"title":"An order based hybrid metaheuristic algorithm for solving optimization problems","authors":"O. Gokalp, Aybars Uğur","doi":"10.1109/UBMK.2017.8093477","DOIUrl":null,"url":null,"abstract":"In this work, a hybrid method that includes metaheuristic algorithms has been proposed for solving optimization problems. The proposed method was implemented as employing three metaheuristic algorithms which are Artificial Bee Colony, Differential Evolution and Particle Swarm Optimization in an order. The success of the developed method is presented by testing on 12 continuous optimization test functions which are widely used in the literature. The experimental results show that the proposed hybrid method gives better results than the individual algorithms that make up it.","PeriodicalId":201903,"journal":{"name":"2017 International Conference on Computer Science and Engineering (UBMK)","volume":"112 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Computer Science and Engineering (UBMK)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/UBMK.2017.8093477","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 work, a hybrid method that includes metaheuristic algorithms has been proposed for solving optimization problems. The proposed method was implemented as employing three metaheuristic algorithms which are Artificial Bee Colony, Differential Evolution and Particle Swarm Optimization in an order. The success of the developed method is presented by testing on 12 continuous optimization test functions which are widely used in the literature. The experimental results show that the proposed hybrid method gives better results than the individual algorithms that make up it.