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1999-11-29Buch DOI: 10.18452/8219
The Sample Average Approximation Method for Stochastic Discrete Optimization
dc.contributor.authorKleywegt, Anton J.
dc.contributor.authorShapiro, Alexander
dc.contributor.editorHigle, Julie L.
dc.contributor.editorRömisch, Werner
dc.contributor.editorSen, Surrajeet
dc.date.accessioned2017-06-16T19:34:46Z
dc.date.available2017-06-16T19:34:46Z
dc.date.created2006-02-08
dc.date.issued1999-11-29
dc.date.submitted1999-11-02
dc.identifier.urihttp://edoc.hu-berlin.de/18452/8871
dc.description.abstractIn this paper we study a Monte Carlo simulation based approach to stochastic discrete optimization problems. The basic idea of such methods is that a random sample is generated and consequently the expected value function is approximated by the corresponding sample average function. The obtained sample average optimization problem is solved, and the procedure is repeated several times until a stopping criterion is satisfied. We discuss convergence rates and stopping rules of this procedure and present a numerical example of the stochastic knapsack problem.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 programmingeng
dc.subjectdiscrete optimizationeng
dc.subjectMonte Carlo samplingeng
dc.subjectlaw of large numberseng
dc.subjectlarge deviations theoryeng
dc.subjectsample average approximationeng
dc.subjectstopping ruleseng
dc.subjectstochastic knapsack problemeng
dc.subject.ddc510 Mathematik
dc.titleThe Sample Average Approximation Method for Stochastic Discrete Optimization
dc.typebook
dc.identifier.urnurn:nbn:de:kobv:11-110-18452/8871-5
dc.identifier.doihttp://dx.doi.org/10.18452/8219
local.edoc.container-titleStochastic Programming E-Print Series
local.edoc.type-nameBuch
local.edoc.container-typeseries
local.edoc.container-type-nameSchriftenreihe
local.edoc.container-publisher-nameSociety for Industrial and Applied Mathematics - SIAM
local.edoc.container-publisher-placePhiladelphia, Pa.
local.edoc.container-volume1999
local.edoc.container-issue3
local.edoc.container-erstkatid2936317-2

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