Hybrid evolutionary algorithm for the Capacitated Centered Clustering Problem


Autoria(s): Chaves, Antonio Augusto; Nogueira Lorena, Luiz Antonio
Contribuinte(s)

Universidade Estadual Paulista (UNESP)

Data(s)

20/05/2014

20/05/2014

01/05/2011

Resumo

The Capacitated Centered Clustering Problem (CCCP) consists of defining a set of p groups with minimum dissimilarity on a network with n points. Demand values are associated with each point and each group has a demand capacity. The problem is well known to be NP-hard and has many practical applications. In this paper, the hybrid method Clustering Search (CS) is implemented to solve the CCCP. This method identifies promising regions of the search space by generating solutions with a metaheuristic, such as Genetic Algorithm, and clustering them into clusters that are then explored further with local search heuristics. Computational results considering instances available in the literature are presented to demonstrate the efficacy of CS. (C) 2010 Elsevier Ltd. All rights reserved.

Formato

5013-5018

Identificador

http://dx.doi.org/10.1016/j.eswa.2010.09.149

Expert Systems With Applications. Oxford: Pergamon-Elsevier B.V. Ltd, v. 38, n. 5, p. 5013-5018, 2011.

0957-4174

http://hdl.handle.net/11449/9379

10.1016/j.eswa.2010.09.149

WOS:000287419900040

Idioma(s)

eng

Publicador

Pergamon-Elsevier B.V. Ltd

Relação

Expert Systems with Applications

Direitos

closedAccess

Palavras-Chave #Clustering problems #Clustering search algorithm #Genetic Algorithm #Metaheuristics
Tipo

info:eu-repo/semantics/article