{"title":"A hybrid genetic algorithm for three-index assignment problem","authors":"Gaofeng Huang, A. Lim","doi":"10.1109/CEC.2003.1299438","DOIUrl":null,"url":null,"abstract":"Three-index assignment problem (AP3) is well-known problem which has been shown to be NP-hard. This problem has been studied extensively, and many exact and heuristic methods have been proposed to solve it. Inspired by the classical assignment problem, we propose a new iterative heuristic, called fragmental optimization (FO), which solves the problem by simplifying it to the assignment problem. We further hybridize our heuristic with the genetic algorithm (GA). Extensive experimental results indicate that our hybrid method to be superior to all previous heuristic methods including those proposed by Balas and Saltzman(1991), Crama and Spieksma(1992), Burkard et al(1996), and Aiex et al(2003).","PeriodicalId":416243,"journal":{"name":"The 2003 Congress on Evolutionary Computation, 2003. CEC '03.","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The 2003 Congress on Evolutionary Computation, 2003. CEC '03.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CEC.2003.1299438","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Three-index assignment problem (AP3) is well-known problem which has been shown to be NP-hard. This problem has been studied extensively, and many exact and heuristic methods have been proposed to solve it. Inspired by the classical assignment problem, we propose a new iterative heuristic, called fragmental optimization (FO), which solves the problem by simplifying it to the assignment problem. We further hybridize our heuristic with the genetic algorithm (GA). Extensive experimental results indicate that our hybrid method to be superior to all previous heuristic methods including those proposed by Balas and Saltzman(1991), Crama and Spieksma(1992), Burkard et al(1996), and Aiex et al(2003).