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2008-07-05Buch DOI: 10.18452/8396
Convergence Analysis of a Weighted Barrier Decomposition Algorithm for Two Stage Stochastic Programming
dc.contributor.authorMehrotra, Sanjay
dc.contributor.authorOzevin, M. Gokhan
dc.contributor.editorHigle, Julie L.
dc.contributor.editorRömisch, Werner
dc.contributor.editorSen, Surrajeet
dc.date.accessioned2017-06-16T20:18:25Z
dc.date.available2017-06-16T20:18:25Z
dc.date.created2008-07-08
dc.date.issued2008-07-05
dc.date.submitted2008-03-01
dc.identifier.urihttp://edoc.hu-berlin.de/18452/9048
dc.description.abstractMehrotra and Ozevin [7] computationally found that a weighted primal barrier decomposition algorithm significantly outperforms the barrier decomposition proposed and analyzed in [11; 6; 8]. Thispaper provides a theoretical foundation for the weighted barrier decomposition algorithm (WBDA)in [7]. Although the worst case analysis of the WBDA achieves a first-stage iteration complexitybound that is worse than the bound shown for the decomposition algorithms of [11] and [6; 8],under a probabilistic assumption we show that the worst case iteration complexity of WBDA isindependent of the number of scenarios in the problem. The probabilistic assumption uses a novelconcept of self-concordant random variables.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.subjecttwo stage stochastic programmingeng
dc.subjectlinear-quadratic programmingeng
dc.subjectBender's decompositioneng
dc.subjectlagre scale optimizationeng
dc.subjectnondifferentiable convex optimizationeng
dc.subject.ddc510 Mathematik
dc.titleConvergence Analysis of a Weighted Barrier Decomposition Algorithm for Two Stage Stochastic Programming
dc.typebook
dc.identifier.urnurn:nbn:de:kobv:11-10090107
dc.identifier.doihttp://dx.doi.org/10.18452/8396
local.edoc.pages36
local.edoc.type-nameBuch
local.edoc.container-typeseries
local.edoc.container-type-nameSchriftenreihe
local.edoc.container-year2007
dc.identifier.zdb2936317-2
dcterms.bibliographicCitation.originalpublisherplaceNorthwestern University, Evanston
bua.series.nameStochastic Programming E-Print Series
bua.series.issuenumber2008,12

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