Stochastic integer programming solution through a convexification method

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dc.contributor.authorCerisola Lopez De Haro, Santiagoes-ES
dc.contributor.authorLatorre Canteli, Jesús Maríaes-ES
dc.contributor.authorRamos Galán, Andréses-ES
dc.date.accessioned2016-10-18T12:05:21Z
dc.date.available2016-10-18T12:05:21Z
dc.description.abstractIn this paper we present a solution method for stochastic integer problems. The method is a Benderstype algorithm that sequentially approximates the nonconvex recourse functions defined by the second stage subproblems. The presented convexification takes into account the domain that is induced by the collection of tender variables. The method is applied to a broad collection of stochastic integer programming problems taken from the literature and a summary of the numerical results is presented.es-ES
dc.description.abstractIn this paper we present a solution method for stochastic integer problems. The method is a Benderstype algorithm that sequentially approximates the nonconvex recourse functions defined by the second stage subproblems. The presented convexification takes into account the domain that is induced by the collection of tender variables. The method is applied to a broad collection of stochastic integer programming problems taken from the literature and a summary of the numerical results is presented.en-GB
dc.description.versioninfo:eu-repo/semantics/draftes_ES
dc.format.mimetypeapplication/pdfes_ES
dc.identifier.urihttp://hdl.handle.net/11531/14181
dc.keywordsBenders decomposition, lagrangean relaxationes-ES
dc.keywordsBenders decomposition, lagrangean relaxationen-GB
dc.language.isoen-GBes_ES
dc.rightses_ES
dc.rights.accessRightsinfo:eu-repo/semantics/restrictedAccesses_ES
dc.rights.uries_ES
dc.titleStochastic integer programming solution through a convexification methodes_ES
dc.typeinfo:eu-repo/semantics/workingPaperes_ES

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