Applying Ant system for solving unequal area facility layout problems
Ant Colony Optimization (ACO) is a young metaheuristic algorithm which has shown promising results in solving many optimization problems. To date, a formal ACO-based metaheuristic has not been applied for solving Unequal Area Facility Layout Problems (UA-FLPs). This paper proposes an Ant System (AS)...
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my.utm.228712018-11-09T08:07:26Z http://eprints.utm.my/id/eprint/22871/ Applying Ant system for solving unequal area facility layout problems Kuan, Yew Wong Komarudin, Komarudin TJ Mechanical engineering and machinery Ant Colony Optimization (ACO) is a young metaheuristic algorithm which has shown promising results in solving many optimization problems. To date, a formal ACO-based metaheuristic has not been applied for solving Unequal Area Facility Layout Problems (UA-FLPs). This paper proposes an Ant System (AS) (one of the ACO variants) to solve them. As a discrete optimization algorithm, the proposed algorithm uses slicing tree representation to easily represent the problems without too restricting the solution space. It uses several types of local search to improve its search performance. It is then tested using several case problems with different size and setting. Overall, the proposed algorithm shows encouraging results in solving UA-FLPs. Elsevier 2010-05-01 Article PeerReviewed Kuan, Yew Wong and Komarudin, Komarudin (2010) Applying Ant system for solving unequal area facility layout problems. European Journal of Operational Research, 202 (3). 730 - 746. ISSN 0377-2217 https://doi.org/10.1016/j.ejor.2009.06.016 DOI:10.1016/j.ejor.2009.06.016 |
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TJ Mechanical engineering and machinery Kuan, Yew Wong Komarudin, Komarudin Applying Ant system for solving unequal area facility layout problems |
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Ant Colony Optimization (ACO) is a young metaheuristic algorithm which has shown promising results in solving many optimization problems. To date, a formal ACO-based metaheuristic has not been applied for solving Unequal Area Facility Layout Problems (UA-FLPs). This paper proposes an Ant System (AS) (one of the ACO variants) to solve them. As a discrete optimization algorithm, the proposed algorithm uses slicing tree representation to easily represent the problems without too restricting the solution space. It uses several types of local search to improve its search performance. It is then tested using several case problems with different size and setting. Overall, the proposed algorithm shows encouraging results in solving UA-FLPs. |
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Kuan, Yew Wong Komarudin, Komarudin |
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Kuan, Yew Wong Komarudin, Komarudin |
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Kuan, Yew Wong |
title |
Applying Ant system for solving unequal area facility layout problems |
title_short |
Applying Ant system for solving unequal area facility layout problems |
title_full |
Applying Ant system for solving unequal area facility layout problems |
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Applying Ant system for solving unequal area facility layout problems |
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Applying Ant system for solving unequal area facility layout problems |
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applying ant system for solving unequal area facility layout problems |
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Elsevier |
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2010 |
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http://eprints.utm.my/id/eprint/22871/ https://doi.org/10.1016/j.ejor.2009.06.016 |
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