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2002-05-03Buch DOI: 10.18452/8272
Higher-Order Upper Bounds on the Expectation of a Convex Function
dc.contributor.authorDokov, Steftcho P.
dc.contributor.authorMorton, David P.
dc.contributor.editorHigle, Julie L.
dc.contributor.editorRömisch, Werner
dc.contributor.editorSen, Surrajeet
dc.date.accessioned2017-06-16T19:47:45Z
dc.date.available2017-06-16T19:47:45Z
dc.date.created2006-02-17
dc.date.issued2002-05-03
dc.date.submitted2002-01-23
dc.identifier.urihttp://edoc.hu-berlin.de/18452/8924
dc.description.abstractWe develop a decreasing sequence of upper bounds on the expectation of a convex function. The n-th term in the sequence uses moments and cross-moments of up to degree n from the underlying random vector. Our work has application to a class of two-stage stochastic programs with recourse. The objective function of such a model can defy computation when: (i) the underlying distribution is assumed to be known only through a limited number of moments or (ii) the function is computationally intractable, even though the distribution is known. A tractable approximating model arises by replacing the objective function by one of our bounding elements. We justify this approach by showing that as n grows, solutions of the order-n approximation solve the true stochastic program.eng
dc.language.isoeng
dc.publisherHumboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät II, Institut für Mathematik
dc.subject.ddc510 Mathematik
dc.titleHigher-Order Upper Bounds on the Expectation of a Convex Function
dc.typebook
dc.identifier.urnurn:nbn:de:kobv:11-10058406
dc.identifier.doihttp://dx.doi.org/10.18452/8272
local.edoc.container-titleStochastic Programming E-Print Series
local.edoc.type-nameBuch
local.edoc.container-typeseries
local.edoc.container-type-nameSchriftenreihe
local.edoc.container-volume2002
local.edoc.container-issue8
local.edoc.container-erstkatid2936317-2

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