Show simple item record

2014-10-16Buch DOI: 10.18452/8442
Dynamic Generation of Scenario Trees
dc.contributor.authorPflug, Georg Ch.
dc.contributor.authorPichler, Alois
dc.contributor.editorHigle, Julie L.
dc.contributor.editorRömisch, Werner
dc.contributor.editorSen, Surrajeet
dc.date.accessioned2017-06-16T20:31:39Z
dc.date.available2017-06-16T20:31:39Z
dc.date.created2014-10-17
dc.date.issued2014-10-16
dc.date.submitted2014-03-14
dc.identifier.urihttp://edoc.hu-berlin.de/18452/9094
dc.description.abstractWe present new algorithms for the dynamic generation of scenario trees for multistagestochastic optimization. The different methods described are based on random vectors, whichare drawn from conditional distributions given the past and on sample trajectories.The structure of the tree is not determined beforehand, but dynamically adapted to meeta distance criterion, which insures the quality of the approximation. The criterion is built ontransportation theory, which is extended to stochastic processes.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.subjectstochastic optimizationeng
dc.subjectdecision treeseng
dc.subjectoptimal transportationeng
dc.subject.ddc510 Mathematik
dc.titleDynamic Generation of Scenario Trees
dc.typebook
dc.identifier.urnurn:nbn:de:kobv:11-100220742
dc.identifier.doihttp://dx.doi.org/10.18452/8442
local.edoc.pages30
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.issuenumber2014,4

Show simple item record