2026-04-19T04:47:11Zhttps://riubu.ubu.es/oai/requestoai:riubu.ubu.es:10259/98222025-05-12T08:02:12Zcom_10259_5645com_10259_5086com_10259_2604col_10259_9820col_10259_5684
Pacheco Bonrostro, Joaquín
410
600
0000-0002-7462-8680
Casado Yusta, Silvia
666
600
0000-0002-9663-1557
2024-12-20T12:19:21Z
2024-12-20T12:19:21Z
2022
http://hdl.handle.net/10259/9822
10.71486/5n2k-c575
Given an undirected graph, a clique is a subset of vertices in which the induced subgraph is complete; that is, all pairs of vertices of this subset are adjacent. Clique problems in graphs are very important due to their numerous applications. One of these problems is the clique partitioning problem (CPP), which consists of dividing the set of vertices of a graph into the smallest number of cliques possible. The CPP is an NP-hard problem with many application fields (timetabling, manufacturing, scheduling, telecommunications, etc.). Despite its great applicability, few recent studies have focused on proposing specific resolution methods for the CPP. This article presents a resolution method that combines multistart strategies with tabu search. The most novel characteristic of our method is that it allows unfeasible solutions to be visited, which facilitates exploration of the solution space. The computational tests show that our method performs better than previous methods proposed for this problem. In fact, our method strictly improves the results of these methods in most of the instances considered while requiring less computation time.
This work was partially supported by FEDER funds and the Spanish State Research Agency (Projects PID2019-104263RB-C44 and PDC2021–121021-C22); the Regional Government of “Castilla y León”, Spain (Project BU071G19); the Regional Government of “Castilla y León”; and FEDER funds (Project BU056P20).
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Universidad de Burgos
http://hdl.handle.net/10259/7402
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-104263RB-C44/ES/MEJORA EN LA TOMA DE DECISIONES EN EL AMBITO DE LA LOGISTICA Y PROBLEMAS RELACIONADOS. ENFOQUE MULTI-OBJETIVO/
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PDC2021-121021-C22/ES/SISTEMAS DE APOYO A LA TOMA DE DECISIONES EFICIENTES: PLANIFICACION DE LA LOGISTICA EXTERNA E INTERNA Y SELECCION DE CARTERAS/
info:eu-repo/grantAgreement/Junta de Castilla y León//BU071G19//Métodos heurísticos para problemas de optimización de recursos sanitarios con varios objetivos/
info:eu-repo/grantAgreement/Junta de Castilla y León//BU056P20//Análisis de problemas de logística sanitaria: Enfoque multi-objetivo y uso de metaheurísticas/
Atribución-NoComercial 4.0 Internacional
http://creativecommons.org/licenses/by-nc/4.0/
info:eu-repo/semantics/openAccess
Clique partitioning problem
Metaheuristics
Tabu search
Multistart methods
Investigación operativa
Modelos matemáticos
Operations research
Mathematical models
Dataset of the paper “A stepped tabu search method for the clique partitioning problem”. Applied Intelligence, 53, 16275-16292
dataset
info:eu-repo/semantics/acceptedVersion
2022
LICENSE
license.txt
license.txt
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https://riubu.ubu.es/bitstream/10259/9822/4/license.txt
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ORIGINAL
readme.docx
readme.docx
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Pacheco-solutions_in_dimacs_instances_for_cpp-2022.zip
Pacheco-solutions_in_dimacs_instances_for_cpp-2022.zip
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10259/9822
oai:riubu.ubu.es:10259/9822
2025-05-12 10:02:12.251
Repositorio Institucional de la Universidad de Burgos
bubrep@ubu.es
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