{"title":"New migration operator in Biogeography-based optimization for solving traveling salesman problem","authors":"Huynh Thi Thanh Binh, Pham Dinh Thanh","doi":"10.1109/TENCON.2016.7847984","DOIUrl":null,"url":null,"abstract":"Traveling salesman problem is a famous discrete optimization problem and has many applications in the real world. Biogeography-based on optimization algorithm (BBO) is a new evolution algorithm inspired by the science of biogcograpln and designed based on the migration strategy of animals. According to investigations and analysis on this algorithm, BBO has great success in numerous optimization problems and it has been used in different types of applications. In BBO, the migration operator is an important operator which is able to efficiently share the good information among solutions. In order to improve the performance of the migration operator, this paper proposes a new migration operator in BBO for solving TSP, The results of BBO using the new operator is compared with that using an existing migration operator on TSP instances from TSP-Lib. Experiment results show that the new migration operator is more effective in terms of quality of solution for most of the data instances.","PeriodicalId":246458,"journal":{"name":"2016 IEEE Region 10 Conference (TENCON)","volume":"158 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE Region 10 Conference (TENCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TENCON.2016.7847984","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Traveling salesman problem is a famous discrete optimization problem and has many applications in the real world. Biogeography-based on optimization algorithm (BBO) is a new evolution algorithm inspired by the science of biogcograpln and designed based on the migration strategy of animals. According to investigations and analysis on this algorithm, BBO has great success in numerous optimization problems and it has been used in different types of applications. In BBO, the migration operator is an important operator which is able to efficiently share the good information among solutions. In order to improve the performance of the migration operator, this paper proposes a new migration operator in BBO for solving TSP, The results of BBO using the new operator is compared with that using an existing migration operator on TSP instances from TSP-Lib. Experiment results show that the new migration operator is more effective in terms of quality of solution for most of the data instances.