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2000-06-26Buch DOI: 10.18452/8239
Conditioning of stochastic programs
dc.contributor.authorShapiro, Alexander
dc.contributor.authorKim, Joocheol
dc.contributor.authorHomem-de-Mello, Tito
dc.contributor.editorHigle, Julie L.
dc.contributor.editorRömisch, Werner
dc.contributor.editorSen, Surrajeet
dc.date.accessioned2017-06-16T19:39:17Z
dc.date.available2017-06-16T19:39:17Z
dc.date.created2006-02-09
dc.date.issued2000-06-26
dc.date.submitted2000-05-24
dc.identifier.urihttp://edoc.hu-berlin.de/18452/8891
dc.description.abstractIn this paper we consider stochastic programming problems where the objective function is given as an expected value function. With an optimal solution of such a (convex) problem we associate a condition number which characterizes well or ill conditioning of the problem. We show that the sample size needed to calculate the optimal solution of such problem with a given probability is approximately proportional to the condition number.eng
dc.language.isoeng
dc.publisherHumboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät II, Institut für Mathematik
dc.subjectMonte Carlo simulationeng
dc.subjectstochastic programmingeng
dc.subjectLarge Deviations theoryeng
dc.subjectill conditioned problemseng
dc.subject.ddc510 Mathematik
dc.titleConditioning of stochastic programs
dc.typebook
dc.identifier.urnurn:nbn:de:kobv:11-10057688
dc.identifier.doihttp://dx.doi.org/10.18452/8239
local.edoc.container-titleStochastic Programming E-Print Series
local.edoc.pages15
local.edoc.type-nameBuch
local.edoc.container-typeseries
local.edoc.container-type-nameSchriftenreihe
local.edoc.container-volume2000
local.edoc.container-issue15
local.edoc.container-erstkatid2936317-2

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