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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Main Authors: LIM, Andrew, LIN, Jing, RODRIGUES, Brian, XIAO, Fei
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Language:English
Published: Institutional Knowledge at Singapore Management University 2006
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Online Access:https://ink.library.smu.edu.sg/lkcsb_research/2619
https://doi.org/10.1016/j.asoc.2005.01.001
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spelling 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
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Bandwidth minimization
Ant colony optimization
Hill climbing
Operations and Supply Chain Management
spellingShingle 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
description 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.
format text
author LIM, Andrew
LIN, Jing
RODRIGUES, Brian
XIAO, Fei
author_facet LIM, Andrew
LIN, Jing
RODRIGUES, Brian
XIAO, Fei
author_sort 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
title_fullStr Ant Colony Optimization with Hill Climbing for the Bandwidth Minimization Problem
title_full_unstemmed Ant Colony Optimization with Hill Climbing for the Bandwidth Minimization Problem
title_sort ant colony optimization with hill climbing for the bandwidth minimization problem
publisher Institutional Knowledge at Singapore Management University
publishDate 2006
url https://ink.library.smu.edu.sg/lkcsb_research/2619
https://doi.org/10.1016/j.asoc.2005.01.001
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