{"title":"基于League Championship算法的离散变量结构优化设计","authors":"A. H. Kashan, S. Jalili, S. Karimiyan","doi":"10.7508/CEIJ.2018.02.002","DOIUrl":null,"url":null,"abstract":"In this paper a league championship algorithm (LCA) is developed for structural optimization where the optimization variables are of discrete type and the set of the values possibly obtained by each variable is also given. LCA is a relatively new metaheuristic algorithm inspired from sport championship process. In LCA, each individual can choose to approach to or retreat from other individuals in the population. This makes it able to provide a good balance between exploration and exploitation tasks in course of the search. To check the suitability and effectiveness of LCA for structural optimization, five benchmark problems are adopted and the performance of LCA is investigated and deeply compared with other approaches. Numerical results indicate that the proposed LCA method is very promising for solving structural optimization problems with discrete variables.","PeriodicalId":43959,"journal":{"name":"Civil Engineering Infrastructures Journal-CEIJ","volume":null,"pages":null},"PeriodicalIF":1.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Optimum Structural Design with Discrete Variables Using League Championship Algorithm\",\"authors\":\"A. H. Kashan, S. Jalili, S. Karimiyan\",\"doi\":\"10.7508/CEIJ.2018.02.002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper a league championship algorithm (LCA) is developed for structural optimization where the optimization variables are of discrete type and the set of the values possibly obtained by each variable is also given. LCA is a relatively new metaheuristic algorithm inspired from sport championship process. In LCA, each individual can choose to approach to or retreat from other individuals in the population. This makes it able to provide a good balance between exploration and exploitation tasks in course of the search. To check the suitability and effectiveness of LCA for structural optimization, five benchmark problems are adopted and the performance of LCA is investigated and deeply compared with other approaches. Numerical results indicate that the proposed LCA method is very promising for solving structural optimization problems with discrete variables.\",\"PeriodicalId\":43959,\"journal\":{\"name\":\"Civil Engineering Infrastructures Journal-CEIJ\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2018-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Civil Engineering Infrastructures Journal-CEIJ\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.7508/CEIJ.2018.02.002\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENGINEERING, CIVIL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Civil Engineering Infrastructures Journal-CEIJ","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.7508/CEIJ.2018.02.002","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
Optimum Structural Design with Discrete Variables Using League Championship Algorithm
In this paper a league championship algorithm (LCA) is developed for structural optimization where the optimization variables are of discrete type and the set of the values possibly obtained by each variable is also given. LCA is a relatively new metaheuristic algorithm inspired from sport championship process. In LCA, each individual can choose to approach to or retreat from other individuals in the population. This makes it able to provide a good balance between exploration and exploitation tasks in course of the search. To check the suitability and effectiveness of LCA for structural optimization, five benchmark problems are adopted and the performance of LCA is investigated and deeply compared with other approaches. Numerical results indicate that the proposed LCA method is very promising for solving structural optimization problems with discrete variables.