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2010-10-19Buch DOI: 10.18452/8413
On joint probabilistic constraints with Gaussian coefficient matrix
dc.contributor.authorAckooij, W. Van
dc.contributor.authorHenrion, R.
dc.contributor.authorMöller, A.
dc.contributor.authorZorgati, R.
dc.contributor.editorHigle, Julie L.
dc.contributor.editorRömisch, Werner
dc.contributor.editorSen, Surrajeet
dc.date.accessioned2017-06-16T20:23:31Z
dc.date.available2017-06-16T20:23:31Z
dc.date.created2010-10-19
dc.date.issued2010-10-19
dc.date.submitted2010-10-09
dc.identifier.urihttp://edoc.hu-berlin.de/18452/9065
dc.description.abstractThe paper deals with joint probabilistic constraints defined by a Gaussiancoefficient matrix. It is shown how to explicitly reduce the computation ofvalues and gradients of the underlying probability function to that of Gaussiandistribution functions. This allows to employ existing efficient algorithms forcalculating this latter class of function in order to solve probabilistically constrainedoptimization problems of the indicated type. Results are illustratedby an example from energy production.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.titleOn joint probabilistic constraints with Gaussian coefficient matrix
dc.typebook
dc.identifier.urnurn:nbn:de:kobv:11-100176216
dc.identifier.doihttp://dx.doi.org/10.18452/8413
local.edoc.container-titleStochastic Programming E-Print Series
local.edoc.pages7
local.edoc.type-nameBuch
local.edoc.container-typeseries
local.edoc.container-type-nameSchriftenreihe
local.edoc.container-volume2010
local.edoc.container-issue6
local.edoc.container-erstkatid2936317-2

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