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A biased random-key genetic algorithm for the minimum quasi-clique partitioning problem

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Autor(es):
Melo, Rafael A. ; Ribeiro, Celso C. ; Riveaux, Jose A.
Número total de Autores: 3
Tipo de documento: Artigo Científico
Fonte: ANNALS OF OPERATIONS RESEARCH; v. N/A, p. 33-pg., 2023-09-28.
Resumo

Let G=(V,E)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$G=(V, E)$$\end{document} be a graph with vertex set V and edge set E, and consider gamma is an element of[0,1)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\gamma \in [0,1)$$\end{document} to be a real constant. A gamma\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\gamma $$\end{document}-clique (or quasi-clique) is a subset V 'subset of V\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$V'\subseteq V$$\end{document} inducing a subgraph of G with edge density at least gamma\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\gamma $$\end{document}. In this paper, we tackle the minimum quasi-clique partitioning problem (MQCPP), which consists of obtaining a minimum-cardinality partition of V into quasi-cliques. We propose a biased random-key genetic algorithm (BRKGA) relying on an efficient partitioning decoder that allows merge operations to combine smaller quasi-cliques into larger ones. Furthermore, we show that MQCPP and the problem of covering the graph with a minimum number of quasi-cliques are not equivalent. Computational experiments indicate that the proposed BRKGA is very effective in obtaining high-quality solutions for MQCPP in low computational times. More specifically, it can at least match all the best solutions available in the literature, strictly improving over them for 20.3% of the benchmark instances. Besides, the approach is robust as it obtains small deviations from the best-achieved solutions when executing multiple independent runs. We also consider the performance of our BRKGA on a new set of challenging large instances with up to 2851 vertices. (AU)

Processo FAPESP: 22/06747-0 - Métodos heurísticos aplicados ao problema multiobjetivo de programação de atividades de técnicos de campo
Beneficiário:José Angel Riveaux Merino
Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado