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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.accessioned2016-01-15T11:17:00Z
dc.date.available2016-01-15T11:17:00Z
dc.date.issued2012-05-01es_ES
dc.identifier.issn0377-2217es_ES
dc.identifier.urihttps:doi.org10.1016j.ejor.2011.11.040es_ES
dc.descriptionArtículos en revistases_ES
dc.description.abstractes-ES
dc.description.abstractIn this paper we apply stochastic dual dynamic programming decomposition to a nonconvex multistage stochastic hydrothermal model where the nonlinear water head effects on production and the nonlinear dependence between the reservoir head and the reservoir volume are modeled. The nonconvex constraints that represent the production function of a hydro plant are approximated by McCormick envelopes. These constraints are split into smaller regions and the McCormick envelopes are used for each region. We use binary variables for this disjunctive programming approach and solve the problem with a decomposition method. We resort to a variant of the L-shaped method for solving the MIP subproblem with binary variables at any stage inside the stochastic dual dynamic programming algorithm. A realistic large-scale case study is presented.en-GB
dc.format.mimetypeapplication/pdfes_ES
dc.language.isoen-GBes_ES
dc.rightses_ES
dc.rights.uries_ES
dc.sourceRevista: European Journal of Operational Research, Periodo: 1, Volumen: online, Número: 3, Página inicial: 687, Página final: 697es_ES
dc.subject.otherInstituto de Investigación Tecnológica (IIT)es_ES
dc.titleStochastic dual dynamic programming applied to nonconvex hydrothermal modelses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.description.versioninfo:eu-repo/semantics/publishedVersiones_ES
dc.rights.accessRightsinfo:eu-repo/semantics/restrictedAccesses_ES
dc.keywordses-ES
dc.keywordsProgramming: Stochastic; Integer; Benders decomposition; Lagrangean relaxation; Stochastic Dual Dynamic Programming; Productionscheduling: planningen-GB


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