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2005-11-11Buch DOI: 10.18452/2673
Global convergence of multidirectional algorithms for unconstrained optimization in normed spaces
dc.contributor.authorGómez, J. A.
dc.contributor.authorRomero, M.
dc.date.accessioned2017-06-15T17:56:07Z
dc.date.available2017-06-15T17:56:07Z
dc.date.created2005-11-11
dc.date.issued2005-11-11none
dc.identifier.urihttp://edoc.hu-berlin.de/18452/3325
dc.description.abstractGlobal convergence theorems for a class of descent methods for unconstrained optimization problems in normed spaces, using multidirectional search, are proved. Exact and inexact search are considered and the results allow to define a globally convergent algoritm for an unconstrained optimal control problem which operates, at each step, on discrete approximations of the original continuous problem.eng
dc.language.isoeng
dc.publisherHumboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät II, Institut für Mathematik
dc.relation.ispartofseriesPreprints aus dem Institut für Mathematik - 5, Mathematik-Preprints, ISSN:0863-0976
dc.subjectMethods of steepest descent typeeng
dc.subjectNonlinear programmingeng
dc.subjectOptimization and variational techniqueseng
dc.subject.ddc510 Mathematik
dc.titleGlobal convergence of multidirectional algorithms for unconstrained optimization in normed spaces
dc.typebook
dc.identifier.urnurn:nbn:de:kobv:11-10053454
dc.identifier.doihttp://dx.doi.org/10.18452/2673
local.edoc.container-titlePreprints aus dem Institut für Mathematik
local.edoc.container-titleMathematik-Preprints
local.edoc.container-issn0863-0976
local.edoc.pages32
local.z-edoc.journal-periodikumAusgabe5,
local.edoc.type-nameBuch
local.edoc.container-typeseries
local.edoc.container-type-nameSchriftenreihe
local.edoc.container-volume1998
local.edoc.container-issue5
local.edoc.container-year1998
local.edoc.container-erstkatid2075199-0

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