Show simple item record

2008-07-02Buch DOI: 10.18452/8395
Numerical Evaluation of Approximation Methods in Stochastic Programming
dc.contributor.authorKüchler, Christian
dc.contributor.authorVigerske, Stefan
dc.contributor.editorHigle, Julie L.
dc.contributor.editorRömisch, Werner
dc.contributor.editorSen, Surrajeet
dc.date.accessioned2017-06-16T20:18:13Z
dc.date.available2017-06-16T20:18:13Z
dc.date.created2008-07-08
dc.date.issued2008-07-02
dc.date.submitted2008-04-28
dc.identifier.urihttp://edoc.hu-berlin.de/18452/9047
dc.description.abstractWe study an approach for the evaluation of approximation and solution methodsfor multistage linear stochastic programs by measuring the performance of the obtained solutions on a set of out-of-sample scenarios. The main point of the approachis to restore the feasibility of solutions to an approximated problem along the out-of-sample scenarios. For this purpose, we consider and compare different feasibilityand optimality based projection methods. With this at hand, we study the quality of solutions to different test models based on classical as well as recombiningscenario trees.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.subjectscenario treeeng
dc.subjectmultistage stochastic programmingeng
dc.subjectout-of-sample evaluationeng
dc.subject.ddc510 Mathematik
dc.titleNumerical Evaluation of Approximation Methods in Stochastic Programming
dc.typebook
dc.identifier.urnurn:nbn:de:kobv:11-10090091
dc.identifier.doihttp://dx.doi.org/10.18452/8395
local.edoc.pages18
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.issuenumber2008,11

Show simple item record