Hybrid evolutionary algorithm for the Capacitated Centered Clustering Problem
Contribuinte(s) |
Universidade Estadual Paulista (UNESP) |
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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 |