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2002-06-04Buch DOI: 10.18452/8275
Integration quadratures in discretization of stochastic programs
dc.contributor.authorPennanen, Teemu
dc.contributor.authorKoivu, Matti
dc.contributor.editorHigle, Julie L.
dc.contributor.editorRömisch, Werner
dc.contributor.editorSen, Surrajeet
dc.date.accessioned2017-06-16T19:48:19Z
dc.date.available2017-06-16T19:48:19Z
dc.date.created2006-02-17
dc.date.issued2002-06-04
dc.date.submitted2002-05-03
dc.identifier.urihttp://edoc.hu-berlin.de/18452/8927
dc.description.abstractBecause of its simplicity, conditional sampling is the most popular method for generating scenario trees in stochastic programming. It is based on approximating probability measures by empirical ones generated by random samples. Because of computational restrictions, these samples cannot be very large, so the empirical measures can be poor approximations of the original ones. This paper shows that modern integration quadratures provide a simple and an attractive alternative to random sampling. These quadratures are designed to give good approximations of given (probability) measures by a small number of quadrature points. The performance of the resulting scenario generation methods is demonstrated by numerical examples.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.subject.ddc510 Mathematik
dc.titleIntegration quadratures in discretization of stochastic programs
dc.typebook
dc.identifier.urnurn:nbn:de:kobv:11-10058449
dc.identifier.urnurn:nbn:de:kobv:11-10058458
dc.identifier.doihttp://dx.doi.org/10.18452/8275
local.edoc.pages16
local.edoc.type-nameBuch
local.edoc.container-typeseries
local.edoc.container-type-nameSchriftenreihe
dc.identifier.zdb2936317-2
bua.series.nameStochastic Programming E-Print Series
bua.series.issuenumber2002,11

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