Ant Colony Optimization with Hill Climbing for the Bandwidth Minimization Problem
In this work, the problem of reducing the bandwidth of sparse matrices by permuting rows and columns is addressed and solved using a hybrid ant system to generate high-quality renumbering which is refined by a hill climbing local search heuristic. Computational experiments compare the algorithm with...
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sg-smu-ink.lkcsb_research-36182016-03-11T14:05:35Z Ant Colony Optimization with Hill Climbing for the Bandwidth Minimization Problem LIM, Andrew LIN, Jing RODRIGUES, Brian XIAO, Fei In this work, the problem of reducing the bandwidth of sparse matrices by permuting rows and columns is addressed and solved using a hybrid ant system to generate high-quality renumbering which is refined by a hill climbing local search heuristic. Computational experiments compare the algorithm with the well-known GPS algorithm, as well as recently proposed methods. These show the new approach to be as good as current best algorithms. In addition, an algorithm to randomly generate matrices with known optimal bandwidth is developed and used to evaluate results. Comparisons show that the new algorithm was able to find either the optimal solution or a solution very close to the optimal for most instances. 2006-01-01T08:00:00Z text https://ink.library.smu.edu.sg/lkcsb_research/2619 info:doi/10.1016/j.asoc.2005.01.001 https://doi.org/10.1016/j.asoc.2005.01.001 Research Collection Lee Kong Chian School Of Business eng Institutional Knowledge at Singapore Management University Bandwidth minimization Ant colony optimization Hill climbing Operations and Supply Chain Management |
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Bandwidth minimization Ant colony optimization Hill climbing Operations and Supply Chain Management LIM, Andrew LIN, Jing RODRIGUES, Brian XIAO, Fei Ant Colony Optimization with Hill Climbing for the Bandwidth Minimization Problem |
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In this work, the problem of reducing the bandwidth of sparse matrices by permuting rows and columns is addressed and solved using a hybrid ant system to generate high-quality renumbering which is refined by a hill climbing local search heuristic. Computational experiments compare the algorithm with the well-known GPS algorithm, as well as recently proposed methods. These show the new approach to be as good as current best algorithms. In addition, an algorithm to randomly generate matrices with known optimal bandwidth is developed and used to evaluate results. Comparisons show that the new algorithm was able to find either the optimal solution or a solution very close to the optimal for most instances. |
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LIM, Andrew LIN, Jing RODRIGUES, Brian XIAO, Fei |
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LIM, Andrew LIN, Jing RODRIGUES, Brian XIAO, Fei |
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LIM, Andrew |
title |
Ant Colony Optimization with Hill Climbing for the Bandwidth Minimization Problem |
title_short |
Ant Colony Optimization with Hill Climbing for the Bandwidth Minimization Problem |
title_full |
Ant Colony Optimization with Hill Climbing for the Bandwidth Minimization Problem |
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Ant Colony Optimization with Hill Climbing for the Bandwidth Minimization Problem |
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Ant Colony Optimization with Hill Climbing for the Bandwidth Minimization Problem |
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ant colony optimization with hill climbing for the bandwidth minimization problem |
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Institutional Knowledge at Singapore Management University |
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2006 |
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https://ink.library.smu.edu.sg/lkcsb_research/2619 https://doi.org/10.1016/j.asoc.2005.01.001 |
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