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dc.contributor.authorJuan Pérez, Angel Alejandro
dc.contributor.authorFaulín, Javier
dc.contributor.authorJorba, Josep
dc.contributor.authorCaceres, J
dc.contributor.authorMarquès Puig, Joan Manel
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Matemàtica Aplicada I
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors
dc.date.accessioned2013-01-14T16:39:55Z
dc.date.created2011
dc.date.issued2011
dc.identifier.citationJuan, A. [et al.]. Using parallel & distributed computing for solving real-time vehicle routing problems with stochastic demands. "Annals of operations research", 2011, núm. June, p. 1-23.
dc.identifier.issn0254-5330
dc.identifier.urihttp://hdl.handle.net/2117/17349
dc.description.abstractThis paper focuses on the Vehicle Routing Problem with Stochastic Demands (VRPSD) and discusses how Parallel and Distributed Computing Systems can be employed to efficiently solve the VRPSD. Our approach deals with uncertainty in the customer demands by considering safety stocks, i.e. when designing the routes, part of the vehicle capacity is reserved to deal with potential emergency situations caused by unexpected demands. Thus, for a given VRPSD instance, our algorithm considers different levels of safety stocks. For each of these levels, a different scenario is defined. Then, the algorithm solves each scenario by integrating Monte Carlo simulation inside a heuristic-randomization process. This way, expected variable costs due to route failures can be naturally estimated even when customers’ demands follow a non-normal probability distribution. Use of parallelization strategies is then considered to run multiple instances of the algorithm in a concurrent way. The resulting concurrent solutions are then compared and the one with the minimum total costs is selected. Two numerical experiments allow analyzing the algorithm’s performance under different parallelization schemas.
dc.format.extent23 p.
dc.language.isoeng
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística::Investigació operativa
dc.subject.lcshOperations research
dc.titleUsing parallel & distributed computing for solving real-time vehicle routing problems with stochastic demands
dc.typeArticle
dc.subject.lemacInvestigació operativa
dc.identifier.doi10.1007/s10479-011-0918-z
dc.description.peerreviewedPeer Reviewed
dc.rights.accessRestricted access - publisher's policy
drac.iddocument11158086
dc.description.versionPostprint (published version)
dc.date.lift10000-01-01
upcommons.citation.authorJuan, A.; Faulín, J.; Jorba, J.; Caceres, J.; Marques, J.
upcommons.citation.publishedtrue
upcommons.citation.publicationNameAnnals of operations research
upcommons.citation.numberJune
upcommons.citation.startingPage1
upcommons.citation.endingPage23


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Except where otherwise noted, content on this work is licensed under a Creative Commons license: Attribution-NonCommercial-NoDerivs 3.0 Spain