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Main Authors: Lima, Júnior R., Santos, Viníicius Gandra M., Carvalho, Marco Antonio M.
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2409.04926
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author Lima, Júnior R.
Santos, Viníicius Gandra M.
Carvalho, Marco Antonio M.
author_facet Lima, Júnior R.
Santos, Viníicius Gandra M.
Carvalho, Marco Antonio M.
contents In this study, a new $Δ$-evaluation method is introduced for solving a column permutation problem defined on a sparse binary matrix with the consecutive ones property. This problem models various $\mathcal{NP}$-hard problems in graph theory and industrial manufacturing contexts. The computational experiments compare the processing time of the $Δ$-evaluation method with two other methods used in well-known local search procedures. The study considers a comprehensive set of instances of well-known problems, such as Gate Matrix Layout and Minimization of Open Stacks. The proposed evaluation method is generally competitive and particularly useful for large and dense instances. It can be easily integrated into local search and metaheuristic algorithms to improve solutions without significantly increasing processing time.
format Preprint
id arxiv_https___arxiv_org_abs_2409_04926
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A $Δ$-evaluation function for column permutation problems
Lima, Júnior R.
Santos, Viníicius Gandra M.
Carvalho, Marco Antonio M.
Artificial Intelligence
Combinatorics
Optimization and Control
90
J.6
In this study, a new $Δ$-evaluation method is introduced for solving a column permutation problem defined on a sparse binary matrix with the consecutive ones property. This problem models various $\mathcal{NP}$-hard problems in graph theory and industrial manufacturing contexts. The computational experiments compare the processing time of the $Δ$-evaluation method with two other methods used in well-known local search procedures. The study considers a comprehensive set of instances of well-known problems, such as Gate Matrix Layout and Minimization of Open Stacks. The proposed evaluation method is generally competitive and particularly useful for large and dense instances. It can be easily integrated into local search and metaheuristic algorithms to improve solutions without significantly increasing processing time.
title A $Δ$-evaluation function for column permutation problems
topic Artificial Intelligence
Combinatorics
Optimization and Control
90
J.6
url https://arxiv.org/abs/2409.04926