New versions of the Hestenes-Stiefel nonlinear conjugate gradient method based on the secant condition for optimization

Detalhes bibliográficos
Autor(a) principal: Zhang,Li
Data de Publicação: 2009
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Computational & Applied Mathematics
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1807-03022009000100006
Resumo: Based on the secant condition often satisfied by quasi-Newton methods, two new versions of the Hestenes-Stiefel (HS) nonlinear conjugate gradient method are proposed, which are descent methods even with inexact line searches. The search directions of the proposed methods have the form d k = - θkg k + βkHSd k-1, or d k = -g k + βkHSd k-1+ θky k-1. When exact line searches are used, the proposed methods reduce to the standard HS method. Convergence properties of the proposed methods are discussed. These results are also extended to some other conjugate gradient methods such as the Polak-Ribiére-Polyak (PRP) method. Numerical results are reported.
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spelling New versions of the Hestenes-Stiefel nonlinear conjugate gradient method based on the secant condition for optimizationHS methoddescent directionglobal convergenceBased on the secant condition often satisfied by quasi-Newton methods, two new versions of the Hestenes-Stiefel (HS) nonlinear conjugate gradient method are proposed, which are descent methods even with inexact line searches. The search directions of the proposed methods have the form d k = - θkg k + βkHSd k-1, or d k = -g k + βkHSd k-1+ θky k-1. When exact line searches are used, the proposed methods reduce to the standard HS method. Convergence properties of the proposed methods are discussed. These results are also extended to some other conjugate gradient methods such as the Polak-Ribiére-Polyak (PRP) method. Numerical results are reported.Sociedade Brasileira de Matemática Aplicada e Computacional2009-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1807-03022009000100006Computational & Applied Mathematics v.28 n.1 2009reponame:Computational & Applied Mathematicsinstname:Sociedade Brasileira de Matemática Aplicada e Computacional (SBMAC)instacron:SBMACinfo:eu-repo/semantics/openAccessZhang,Lieng2009-03-30T00:00:00Zoai:scielo:S1807-03022009000100006Revistahttps://www.scielo.br/j/cam/ONGhttps://old.scielo.br/oai/scielo-oai.php||sbmac@sbmac.org.br1807-03022238-3603opendoar:2009-03-30T00:00Computational & Applied Mathematics - Sociedade Brasileira de Matemática Aplicada e Computacional (SBMAC)false
dc.title.none.fl_str_mv New versions of the Hestenes-Stiefel nonlinear conjugate gradient method based on the secant condition for optimization
title New versions of the Hestenes-Stiefel nonlinear conjugate gradient method based on the secant condition for optimization
spellingShingle New versions of the Hestenes-Stiefel nonlinear conjugate gradient method based on the secant condition for optimization
Zhang,Li
HS method
descent direction
global convergence
title_short New versions of the Hestenes-Stiefel nonlinear conjugate gradient method based on the secant condition for optimization
title_full New versions of the Hestenes-Stiefel nonlinear conjugate gradient method based on the secant condition for optimization
title_fullStr New versions of the Hestenes-Stiefel nonlinear conjugate gradient method based on the secant condition for optimization
title_full_unstemmed New versions of the Hestenes-Stiefel nonlinear conjugate gradient method based on the secant condition for optimization
title_sort New versions of the Hestenes-Stiefel nonlinear conjugate gradient method based on the secant condition for optimization
author Zhang,Li
author_facet Zhang,Li
author_role author
dc.contributor.author.fl_str_mv Zhang,Li
dc.subject.por.fl_str_mv HS method
descent direction
global convergence
topic HS method
descent direction
global convergence
description Based on the secant condition often satisfied by quasi-Newton methods, two new versions of the Hestenes-Stiefel (HS) nonlinear conjugate gradient method are proposed, which are descent methods even with inexact line searches. The search directions of the proposed methods have the form d k = - θkg k + βkHSd k-1, or d k = -g k + βkHSd k-1+ θky k-1. When exact line searches are used, the proposed methods reduce to the standard HS method. Convergence properties of the proposed methods are discussed. These results are also extended to some other conjugate gradient methods such as the Polak-Ribiére-Polyak (PRP) method. Numerical results are reported.
publishDate 2009
dc.date.none.fl_str_mv 2009-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1807-03022009000100006
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1807-03022009000100006
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Sociedade Brasileira de Matemática Aplicada e Computacional
publisher.none.fl_str_mv Sociedade Brasileira de Matemática Aplicada e Computacional
dc.source.none.fl_str_mv Computational & Applied Mathematics v.28 n.1 2009
reponame:Computational & Applied Mathematics
instname:Sociedade Brasileira de Matemática Aplicada e Computacional (SBMAC)
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reponame_str Computational & Applied Mathematics
collection Computational & Applied Mathematics
repository.name.fl_str_mv Computational & Applied Mathematics - Sociedade Brasileira de Matemática Aplicada e Computacional (SBMAC)
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