You are in the accessibility menu

Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/72758
Full metadata record
DC FieldValueLanguage
dc.contributor.authorLuiz Usberti, Fábio-
dc.contributor.authorMorelato França, Paulo-
dc.contributor.authorFrança, André Luiz Morelato-
dc.date.accessioned2014-05-27T11:26:06Z-
dc.date.accessioned2016-10-25T18:34:57Z-
dc.date.available2014-05-27T11:26:06Z-
dc.date.available2016-10-25T18:34:57Z-
dc.date.issued2011-10-31-
dc.identifierhttp://dx.doi.org/10.1016/j.cor.2011.10.014-
dc.identifier.citationComputers and Operations Research.-
dc.identifier.issn0305-0548-
dc.identifier.urihttp://hdl.handle.net/11449/72758-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/72758-
dc.description.abstractThe Capacitated Arc Routing Problem (CARP) is a well-known NP-hard combinatorial optimization problem where, given an undirected graph, the objective is to find a minimum cost set of tours servicing a subset of required edges under vehicle capacity constraints. There are numerous applications for the CARP, such as street sweeping, garbage collection, mail delivery, school bus routing, and meter reading. A Greedy Randomized Adaptive Search Procedure (GRASP) with Path-Relinking (PR) is proposed and compared with other successful CARP metaheuristics. Some features of this GRASP with PR are (i) reactive parameter tuning, where the parameter value is stochastically selected biased in favor of those values which historically produced the best solutions in average; (ii) a statistical filter, which discard initial solutions if they are unlikely to improve the incumbent best solution; (iii) infeasible local search, where high-quality solutions, though infeasible, are used to explore the feasible/infeasible boundaries of the solution space; (iv) evolutionary PR, a recent trend where the pool of elite solutions is progressively improved by successive relinking of pairs of elite solutions. Computational tests were conducted using a set of 81 instances, and results reveal that the GRASP is very competitive, achieving the best overall deviation from lower bounds and the highest number of best solutions found. © 2011 Elsevier Ltd. All rights reserved.en
dc.language.isoeng-
dc.sourceScopus-
dc.subjectArc routing-
dc.subjectEvolutionary path-relinking-
dc.subjectGRASP filtering-
dc.subjectInfeasible solution space search-
dc.subjectMetaheuristics-
dc.subjectReactive parameters-
dc.titleGRASP with evolutionary path-relinking for the capacitated arc routing problemen
dc.typeoutro-
dc.contributor.institutionUniversidade Estadual de Campinas (UNICAMP)-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.identifier.doi10.1016/j.cor.2011.10.014-
dc.identifier.wosWOS:000326610000037-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartofComputers and Operations Research-
dc.identifier.scopus2-s2.0-80054966397-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

There are no files associated with this item.
 

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.