Heuristics For A Hub Location-routing Problem

dc.creatorLopes
dc.creatorMauro Cardoso; de Andrade
dc.creatorCarlos Eduardo; de Queiroz
dc.creatorThiago Alves; Resende
dc.creatorMauricio G. C.; Miyazawa
dc.creatorFlavio Keidi
dc.date2016
dc.dateagos
dc.date2017-11-13T11:33:35Z
dc.date2017-11-13T11:33:35Z
dc.date.accessioned2018-03-29T05:48:01Z
dc.date.available2018-03-29T05:48:01Z
dc.identifierNetworks. Wiley-blackwell, v. 68, p. 54 - 90, 2016.
dc.identifier0028-3045
dc.identifier1097-0037
dc.identifierWOS:000379914900005
dc.identifier10.1002/net.21685
dc.identifierhttp://onlinelibrary-wiley-com.ez88.periodicos.capes.gov.br/doi/10.1002/net.21685/full
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/326296
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1363302
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.descriptionWe investigate a variant of the many-to-many hub location-routing problem which consists in partitioning the set of nodes of a graph into routes containing exactly one hub each, and determining an extra route interconnecting all hubs. A variable neighborhood descent with neighborhood structures based on remove/add, swap and exchange moves nested with routing and location operations is used as a local search procedure in a multistart algorithm. We also consider a sequential version of this local search in the multistart. In addition, a biased random-key genetic algorithm working with a local search routine, which also considers routing and location operations, is applied to the problem. To compare the heuristic solutions, we develop an integer programming formulation which is solved with a branch-andcut algorithm. Capacity and path elimination constraints are added in a cutting plane fashion. The separation algorithms are based on the computation of min-cut trees and on the connected components of a support graph. Computational experiments were conducted on several benchmark instances of routing problems and show that the heuristics are effective on medium to large-sized instances, while the branch-and-cut algorithm solves small to medium sized problems to optimality. These algorithms were also compared with a commercial hybrid solver showing that the heuristics are quite competitive. (C) 2016 Wiley Periodicals, Inc.
dc.description68
dc.description1
dc.description54
dc.description90
dc.descriptionCNPq
dc.descriptionFAPESP
dc.descriptionFAPEG
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.languageEnglish
dc.publisherWiley-Blackwell
dc.publisherHoboken
dc.relationNetworks
dc.rightsfechado
dc.sourceWOS
dc.subjectHub Location-routing Problem
dc.subjectHeuristics
dc.subjectVariable Neighborhood Descent
dc.subjectBiased Random-key Genetic Algorithm
dc.subjectInteger Formulation
dc.titleHeuristics For A Hub Location-routing Problem
dc.typeArtículos de revistas


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