Stochastic integer programming solution through a convexification method

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Campo DC	Valor	Lengua/Idioma
dc.contributor.author	Cerisola Lopez De Haro, Santiago	es-ES
dc.contributor.author	Latorre Canteli, Jesús María	es-ES
dc.contributor.author	Ramos Galán, Andrés	es-ES
dc.date.accessioned	2016-10-18T12:05:21Z	-
dc.date.available	2016-10-18T12:05:21Z	-
dc.identifier.uri	http://hdl.handle.net/11531/14181	-
dc.description.abstract		es-ES
dc.description.abstract	In 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.format.mimetype	application/pdf	es_ES
dc.language.iso	en-GB	es_ES
dc.rights		es_ES
dc.rights.uri		es_ES
dc.title	Stochastic integer programming solution through a convexification method	es_ES
dc.type	info:eu-repo/semantics/workingPaper	es_ES
dc.description.version	info:eu-repo/semantics/draft	es_ES
dc.rights.accessRights	info:eu-repo/semantics/restrictedAccess	es_ES
dc.keywords		es-ES
dc.keywords	Benders decomposition, lagrangean relaxation	en-GB
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