{"title":"一种基于顺序的混合元启发式算法求解优化问题","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":"{\"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}","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}
An order based hybrid metaheuristic algorithm for solving optimization problems
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.