A filter SQP algorithm without a feasibility restoration phase

Detalhes bibliográficos
Autor(a) principal: Shen,Chungen
Data de Publicação: 2009
Outros Autores: Xue,Wenjuan, Pu,Dingguo
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Computational & Applied Mathematics
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1807-03022009000200003
Resumo: In this paper we present a filter sequential quadratic programming (SQP) algorithm for solving constrained optimization problems. This algorithm is based on the modified quadratic programming (QP) subproblem proposed by Burke and Han, and it can avoid the infeasibility of the QP subproblem at each iteration. Compared with other filter SQP algorithms, our algorithm does not require any restoration phase procedure which may spend a large amount of computation. We underline that global convergence is derived without assuming any constraint qualifications. Preliminary numerical results are reported.
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spelling A filter SQP algorithm without a feasibility restoration phasefilterSQPconstrained optimizationrestoration phaseIn this paper we present a filter sequential quadratic programming (SQP) algorithm for solving constrained optimization problems. This algorithm is based on the modified quadratic programming (QP) subproblem proposed by Burke and Han, and it can avoid the infeasibility of the QP subproblem at each iteration. Compared with other filter SQP algorithms, our algorithm does not require any restoration phase procedure which may spend a large amount of computation. We underline that global convergence is derived without assuming any constraint qualifications. Preliminary 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=S1807-03022009000200003Computational & Applied Mathematics v.28 n.2 2009reponame:Computational & Applied Mathematicsinstname:Sociedade Brasileira de Matemática Aplicada e Computacional (SBMAC)instacron:SBMAC10.1590/S1807-03022009000200003info:eu-repo/semantics/openAccessShen,ChungenXue,WenjuanPu,Dingguoeng2009-07-08T00:00:00Zoai:scielo:S1807-03022009000200003Revistahttps://www.scielo.br/j/cam/ONGhttps://old.scielo.br/oai/scielo-oai.php||sbmac@sbmac.org.br1807-03022238-3603opendoar:2009-07-08T00:00Computational & Applied Mathematics - Sociedade Brasileira de Matemática Aplicada e Computacional (SBMAC)false
dc.title.none.fl_str_mv A filter SQP algorithm without a feasibility restoration phase
title A filter SQP algorithm without a feasibility restoration phase
spellingShingle A filter SQP algorithm without a feasibility restoration phase
Shen,Chungen
filter
SQP
constrained optimization
restoration phase
title_short A filter SQP algorithm without a feasibility restoration phase
title_full A filter SQP algorithm without a feasibility restoration phase
title_fullStr A filter SQP algorithm without a feasibility restoration phase
title_full_unstemmed A filter SQP algorithm without a feasibility restoration phase
title_sort A filter SQP algorithm without a feasibility restoration phase
author Shen,Chungen
author_facet Shen,Chungen
Xue,Wenjuan
Pu,Dingguo
author_role author
author2 Xue,Wenjuan
Pu,Dingguo
author2_role author
author
dc.contributor.author.fl_str_mv Shen,Chungen
Xue,Wenjuan
Pu,Dingguo
dc.subject.por.fl_str_mv filter
SQP
constrained optimization
restoration phase
topic filter
SQP
constrained optimization
restoration phase
description In this paper we present a filter sequential quadratic programming (SQP) algorithm for solving constrained optimization problems. This algorithm is based on the modified quadratic programming (QP) subproblem proposed by Burke and Han, and it can avoid the infeasibility of the QP subproblem at each iteration. Compared with other filter SQP algorithms, our algorithm does not require any restoration phase procedure which may spend a large amount of computation. We underline that global convergence is derived without assuming any constraint qualifications. Preliminary 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=S1807-03022009000200003
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1807-03022009000200003
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S1807-03022009000200003
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.2 2009
reponame:Computational & Applied Mathematics
instname:Sociedade Brasileira de Matemática Aplicada e Computacional (SBMAC)
instacron:SBMAC
instname_str Sociedade Brasileira de Matemática Aplicada e Computacional (SBMAC)
instacron_str SBMAC
institution SBMAC
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)
repository.mail.fl_str_mv ||sbmac@sbmac.org.br
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