{"title":"Hybrid Ant colony System for solving Quadratic Assignment Formulation of Machine Layout Problems","authors":"A. Ramkumar, S. Ponnambalam","doi":"10.1109/ICCIS.2006.252286","DOIUrl":null,"url":null,"abstract":"The quadratic assignment problems (QAPs) are the problem of assigning 'n' facilities to 'n' locations so that the assignment cost is minimized, where the cost is defined by a quadratic function. In this paper we investigate and present the application of population based hybrid ant-colony system (PHAS) metaheuristic for solving machine (facility) layout problems formulated as quadratic assignment problem, a well-known NP hard combinatorial optimization problem. Ant-colony system is a model for designing metaheuristic algorithms for combinatorial optimization problems. The PHAS ant system algorithm incorporates population-based ants in its initial phase instead of small number of ants and probability based pheromone trail modification. We tested our algorithm on the benchmark instances of QAPLIB, a well-known library of QAP instances and the obtained solution quality is compared with solution obtained with standard guided local search algorithm for the same QAP","PeriodicalId":296028,"journal":{"name":"2006 IEEE Conference on Cybernetics and Intelligent Systems","volume":"56 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 IEEE Conference on Cybernetics and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIS.2006.252286","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 19
Abstract
The quadratic assignment problems (QAPs) are the problem of assigning 'n' facilities to 'n' locations so that the assignment cost is minimized, where the cost is defined by a quadratic function. In this paper we investigate and present the application of population based hybrid ant-colony system (PHAS) metaheuristic for solving machine (facility) layout problems formulated as quadratic assignment problem, a well-known NP hard combinatorial optimization problem. Ant-colony system is a model for designing metaheuristic algorithms for combinatorial optimization problems. The PHAS ant system algorithm incorporates population-based ants in its initial phase instead of small number of ants and probability based pheromone trail modification. We tested our algorithm on the benchmark instances of QAPLIB, a well-known library of QAP instances and the obtained solution quality is compared with solution obtained with standard guided local search algorithm for the same QAP
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