dc.contributor | Instituto Nacional de Pesquisas Espaciais (INPE) | |
dc.contributor | Universidade Estadual Paulista (Unesp) | |
dc.date.accessioned | 2014-05-20T13:28:14Z | |
dc.date.available | 2014-05-20T13:28:14Z | |
dc.date.created | 2014-05-20T13:28:14Z | |
dc.date.issued | 2011-05-01 | |
dc.identifier | Expert Systems With Applications. Oxford: Pergamon-Elsevier B.V. Ltd, v. 38, n. 5, p. 5013-5018, 2011. | |
dc.identifier | 0957-4174 | |
dc.identifier | http://hdl.handle.net/11449/9379 | |
dc.identifier | 10.1016/j.eswa.2010.09.149 | |
dc.identifier | WOS:000287419900040 | |
dc.description.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. | |
dc.language | eng | |
dc.publisher | Pergamon-Elsevier B.V. Ltd | |
dc.relation | Expert Systems with Applications | |
dc.relation | 3.768 | |
dc.relation | 1,271 | |
dc.rights | Acesso restrito | |
dc.source | Web of Science | |
dc.subject | Clustering problems | |
dc.subject | Clustering search algorithm | |
dc.subject | Genetic Algorithm | |
dc.subject | Metaheuristics | |
dc.title | Hybrid evolutionary algorithm for the Capacitated Centered Clustering Problem | |
dc.type | Artículos de revistas | |