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2005-11-15Buch DOI: 10.18452/2693
On Stochastic Integer Programming under Probabilistic Constraints
dc.contributor.authorDentcheva, Darinka
dc.contributor.authorPrékopa, András
dc.contributor.authorRuszczynski, Andrzej
dc.date.accessioned2017-06-15T17:59:59Z
dc.date.available2017-06-15T17:59:59Z
dc.date.created2005-11-15
dc.date.issued2005-11-15
dc.identifier.issn0863-0976
dc.identifier.urihttp://edoc.hu-berlin.de/18452/3345
dc.description.abstractWe consider stochastic programming problems with probabilistic constraints involving integer-valued random variables. The concept of p-efficient points of a probability distribution is used to derive various equivalent problem formulations. Next we modify the concept of r-concave discrete probability distributions and analyse its relevance for problems under consideration. These notions are used to derive new lower and upper bounds for the optimal value of probabilistically constrained stochastic programming problems with integer random variables. We also show how limited information about the distribution can be used to construct such bounds.eng
dc.language.isoeng
dc.publisherHumboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät II, Institut für Mathematik
dc.subjectStochastic programmingeng
dc.subject.ddc510 Mathematik
dc.titleOn Stochastic Integer Programming under Probabilistic Constraints
dc.typebook
dc.identifier.urnurn:nbn:de:kobv:11-10053674
dc.identifier.doihttp://dx.doi.org/10.18452/2693
local.edoc.container-titlePreprints aus dem Institut für Mathematik
local.edoc.pages18
local.edoc.type-nameBuch
local.edoc.container-typeseries
local.edoc.container-type-nameSchriftenreihe
local.edoc.container-volume1998
local.edoc.container-issue28
local.edoc.container-year1998
local.edoc.container-erstkatid2075199-0

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