Combining search directions using gradient flows

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Show simple item record Moguerza, Javier M. Prieto, Francisco J. 2012-07-13T11:13:39Z 2012-07-13T11:13:39Z 2003-06
dc.identifier.bibliographicCitation Mathematical Programming A, 2003, v. 96, n. 3, p. 529-559
dc.identifier.issn 0025-5610
dc.description The original publication is available at
dc.description.abstract The efficient combination of directions is a significant problem in line search methods that either use negative curvature, or wish to include additional information such as the gradient or different approximations to the Newton direction. In this paper we describe a new procedure to combine several of these directions within an interior-point primal-dual algorithm. Basically, we combine in an efficient manner a modified Newton direction with the gradient of a merit function and a direction of negative curvature, if it exists.We also show that the procedure is well-defined, and it has reasonable theoretical properties regarding the rate of convergence of the method. We also present numerical results from an implementation of the proposed algorithm on a set of small test problems from the CUTE collection.
dc.description.sponsorship Research supported by Spanish MEC grants BEC2000-0167 and PB98-0728
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Springer
dc.subject.other Negative curvature
dc.subject.other Primal-dual methods
dc.subject.other Interior-point methods
dc.subject.other Nonconvex optimization
dc.subject.other Line searches
dc.title Combining search directions using gradient flows
dc.type article
dc.description.status Publicado
dc.subject.eciencia Estadística
dc.identifier.doi 10.1007/s10107-002-0367-1
dc.rights.accessRights openAccess
dc.type.version acceptedVersion
dc.identifier.publicationfirstpage 529
dc.identifier.publicationissue 3
dc.identifier.publicationlastpage 559
dc.identifier.publicationtitle aMathematical Programming A
dc.identifier.publicationvolume 96
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