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dc.creatorBlanco Izquierdo, Víctores
dc.creatorFernández Aréizaga, Elenaes
dc.creatorPuerto Albandoz, Justoes
dc.date.accessioned2017-06-22T08:02:35Z
dc.date.available2017-06-22T08:02:35Z
dc.date.issued2017-11-01
dc.identifier.citationBlanco Izquierdo, V., Fernández Areizaga, E. y Puerto Albandoz, J. (2017). Minimum Spanning Trees with neighborhoods: Mathematical programming formulations and solution methods. European Journal of Operational Research, 262 (3), 863-878.
dc.identifier.issn0377-2217es
dc.identifier.urihttp://hdl.handle.net/11441/61450
dc.description.abstractThis paper studies Minimum Spanning Trees under incomplete information for its vertices. We assume that no information is available on the precise placement of vertices so that it is only known that vertices belong to some neighborhoods that are second order cone representable and distances are measured with a ℓq-norm. Two mixed integer non linear mathematical programming formulations are presented, based on alternative representations of subtour elimination constraints. A solution scheme is also proposed, resulting from a reformulation suitable for a Benders-like decomposition, which is embedded within an exact branch-and-cut framework. Furthermore, a mathheuristic is developed, which alternates in solving convex subproblems in different solution spaces, and is able to solve larger instances. The results of extensive computational experiments are reported and analyzed.es
dc.description.sponsorshipMinisterio de Economía y Competitividades
dc.formatapplication/pdfes
dc.language.isoenges
dc.publisherElsevieres
dc.relation.ispartofEuropean Journal of Operational Research, 262 (3), 863-878.
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectMinimum spanning treeses
dc.subjectNeighborhoodses
dc.subjectMixed integer non linear programminges
dc.subjectSecond order cone programminges
dc.titleMinimum spanning trees with neighborhoods: mathematical programming formulations and solution methodses
dc.typeinfo:eu-repo/semantics/articlees
dcterms.identifierhttps://ror.org/03yxnpp24
dc.type.versioninfo:eu-repo/semantics/submittedVersiones
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Estadística e Investigación Operativaes
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO/MTM2016-74983-C2-1-Res
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO/MTM2015-63779-Res
dc.relation.publisherversionhttp://ac.els-cdn.com/S0377221717303569/1-s2.0-S0377221717303569-main.pdf?_tid=39e19780-571e-11e7-a8dc-00000aacb360&acdnat=1498117479_857be2b947ca88f8fc7938de9b973341es
dc.identifier.doi10.1016/j.ejor.2017.04.023es
dc.contributor.groupUniversidad de Sevilla. FQM331: Métodos y Modelos de la Estadística y la Investigación Operativaes
idus.format.extent26 p.es
dc.journaltitleEuropean Journal of Operational Researches
dc.publication.volumen262es
dc.publication.issue3es
dc.publication.initialPage863es
dc.publication.endPage878es
dc.contributor.funderMinisterio de Economía y Competitividad (MINECO). España

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