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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/9379
Title: 
Hybrid evolutionary algorithm for the Capacitated Centered Clustering Problem
Author(s): 
Institution: 
  • Instituto Nacional de Pesquisas Espaciais (INPE)
  • Universidade Estadual Paulista (UNESP)
ISSN: 
0957-4174
Abstract: 
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.
Issue Date: 
1-May-2011
Citation: 
Expert Systems With Applications. Oxford: Pergamon-Elsevier B.V. Ltd, v. 38, n. 5, p. 5013-5018, 2011.
Time Duration: 
5013-5018
Publisher: 
Pergamon-Elsevier B.V. Ltd
Keywords: 
  • Clustering problems
  • Clustering search algorithm
  • Genetic Algorithm
  • Metaheuristics
Source: 
http://dx.doi.org/10.1016/j.eswa.2010.09.149
URI: 
Access Rights: 
Acesso restrito
Type: 
outro
Source:
http://repositorio.unesp.br/handle/11449/9379
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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