Huynh Thi Thanh Binh, R. McKay, N. X. Hoai, N. D. Nghia
{"title":"New heuristic and hybrid genetic algorithm for solving the bounded diameter minimum spanning tree problem","authors":"Huynh Thi Thanh Binh, R. McKay, N. X. Hoai, N. D. Nghia","doi":"10.1145/1569901.1569953","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a new heuristic, called Center-Based Recursive Clustering - CBRC, for solving the bounded diameter minimum spanning tree (BDMST) problem. Our proposed hybrid genetic algorithm [12] is also extended to include the new heuristic and a multi-parent crossover operator. We test the new heuristic and genetic algorithm on two sets of benchmark problem instances for the Euclidean and Non-Euclidean cases. Experimental results show the effectiveness of the proposed heuristic and genetic algorithm.","PeriodicalId":193093,"journal":{"name":"Proceedings of the 11th Annual conference on Genetic and evolutionary computation","volume":"140 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 11th Annual conference on Genetic and evolutionary computation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1569901.1569953","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12
Abstract
In this paper, we propose a new heuristic, called Center-Based Recursive Clustering - CBRC, for solving the bounded diameter minimum spanning tree (BDMST) problem. Our proposed hybrid genetic algorithm [12] is also extended to include the new heuristic and a multi-parent crossover operator. We test the new heuristic and genetic algorithm on two sets of benchmark problem instances for the Euclidean and Non-Euclidean cases. Experimental results show the effectiveness of the proposed heuristic and genetic algorithm.