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2000-12-19Buch DOI: 10.18452/8250
The C 3 theorem and a D 2 algorithm for large scale stochastic integer programming
dc.contributor.authorSen, Suvrajeet
dc.contributor.authorHigle, Julia L.
dc.contributor.editorHigle, Julie L.
dc.contributor.editorRömisch, Werner
dc.contributor.editorSen, Surrajeet
dc.date.accessioned2017-06-16T19:41:22Z
dc.date.available2017-06-16T19:41:22Z
dc.date.created2006-02-10
dc.date.issued2000-12-19
dc.date.submitted2000-10-10
dc.identifier.urihttp://edoc.hu-berlin.de/18452/8902
dc.description.abstractThis paper considers the two stage stochastic integer programming problems, with an emphasis on problems in which integer variables appear in the second stage. Drawing heavily on the theory of disjunctive programming, we characterize convexifications of the second stage problem and develop a decomposition-based algorithm for the solution of such problems. In particular, we verify that problems with fixed recourse are characterized by scenario-dependent second stage convexifications that have a great deal in common. We refer to this characterization as the C^3 (Common Cut Coefficients) Theorem. Based on the C^3 Theorem, we develop an algorithmic methodology that we refer to as Disjunctive Decomposition (D^2). We show that when the second stage consists of 0-1 MILP problems , we can obtain accurate second stage objective function estimates afer finitely many steps. We also set the stage for comparisions between problems in which the first stage includes only 0-1 variables and those that allow both continuous and integer variables in the first stage.eng
dc.language.isoeng
dc.publisherHumboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät II, Institut für Mathematik
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectStochastic Mixed-Integer Programmingeng
dc.subjectDisjunctive Programmingeng
dc.subjectCutting Plane Algorithmseng
dc.subject.ddc510 Mathematik
dc.titleThe C 3 theorem and a D 2 algorithm for large scale stochastic integer programming
dc.typebook
dc.identifier.urnurn:nbn:de:kobv:11-110-18452/8902-0
dc.identifier.doihttp://dx.doi.org/10.18452/8250
local.edoc.type-nameBuch
local.edoc.container-typeseries
local.edoc.container-type-nameSchriftenreihe
local.edoc.container-year2005
dc.title.subtitleSet convexification
dc.identifier.zdb2936317-2
dcterms.bibliographicCitation.originalpublishernameSpringer
dcterms.bibliographicCitation.originalpublisherplaceBerlin [u.a.]
bua.series.nameStochastic Programming E-Print Series
bua.series.issuenumber2000,26

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