A sequential quadratic programming algorithm that combines merit function and filter ideas

Detalhes bibliográficos
Autor(a) principal: Gomes,Francisco A.M.
Data de Publicação: 2007
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Computational & Applied Mathematics
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1807-03022007000300003
Resumo: A sequential quadratic programming algorithm for solving nonlinear programming problems is presented. The new feature of the algorithm is related to the definition of the merit function. Instead of using one penalty parameter per iteration and increasing it as the algorithm progresses, we suggest that a new point is to be accepted if it stays sufficiently below the piecewise linear function defined by some previous iterates on the (f,||C||2²)-space. Therefore, the penalty parameter is allowed to decrease between successive iterations. Besides, one need not to decide how to update the penalty parameter. This approach resembles the filter method introduced by Fletcher and Leyffer [Math. Program., 91 (2001), pp. 239-269], but it is less tolerant since a merit function is still used. Numerical comparison with standard methods shows that this strategy is promising.
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spelling A sequential quadratic programming algorithm that combines merit function and filter ideassequential quadratic programmingmerit functionsfilter methodsA sequential quadratic programming algorithm for solving nonlinear programming problems is presented. The new feature of the algorithm is related to the definition of the merit function. Instead of using one penalty parameter per iteration and increasing it as the algorithm progresses, we suggest that a new point is to be accepted if it stays sufficiently below the piecewise linear function defined by some previous iterates on the (f,||C||2²)-space. Therefore, the penalty parameter is allowed to decrease between successive iterations. Besides, one need not to decide how to update the penalty parameter. This approach resembles the filter method introduced by Fletcher and Leyffer [Math. Program., 91 (2001), pp. 239-269], but it is less tolerant since a merit function is still used. Numerical comparison with standard methods shows that this strategy is promising.Sociedade Brasileira de Matemática Aplicada e Computacional2007-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1807-03022007000300003Computational & Applied Mathematics v.26 n.3 2007reponame:Computational & Applied Mathematicsinstname:Sociedade Brasileira de Matemática Aplicada e Computacional (SBMAC)instacron:SBMAC10.1590/S0101-82052007000300003info:eu-repo/semantics/openAccessGomes,Francisco A.M.eng2007-11-22T00:00:00Zoai:scielo:S1807-03022007000300003Revistahttps://www.scielo.br/j/cam/ONGhttps://old.scielo.br/oai/scielo-oai.php||sbmac@sbmac.org.br1807-03022238-3603opendoar:2007-11-22T00:00Computational & Applied Mathematics - Sociedade Brasileira de Matemática Aplicada e Computacional (SBMAC)false
dc.title.none.fl_str_mv A sequential quadratic programming algorithm that combines merit function and filter ideas
title A sequential quadratic programming algorithm that combines merit function and filter ideas
spellingShingle A sequential quadratic programming algorithm that combines merit function and filter ideas
Gomes,Francisco A.M.
sequential quadratic programming
merit functions
filter methods
title_short A sequential quadratic programming algorithm that combines merit function and filter ideas
title_full A sequential quadratic programming algorithm that combines merit function and filter ideas
title_fullStr A sequential quadratic programming algorithm that combines merit function and filter ideas
title_full_unstemmed A sequential quadratic programming algorithm that combines merit function and filter ideas
title_sort A sequential quadratic programming algorithm that combines merit function and filter ideas
author Gomes,Francisco A.M.
author_facet Gomes,Francisco A.M.
author_role author
dc.contributor.author.fl_str_mv Gomes,Francisco A.M.
dc.subject.por.fl_str_mv sequential quadratic programming
merit functions
filter methods
topic sequential quadratic programming
merit functions
filter methods
description A sequential quadratic programming algorithm for solving nonlinear programming problems is presented. The new feature of the algorithm is related to the definition of the merit function. Instead of using one penalty parameter per iteration and increasing it as the algorithm progresses, we suggest that a new point is to be accepted if it stays sufficiently below the piecewise linear function defined by some previous iterates on the (f,||C||2²)-space. Therefore, the penalty parameter is allowed to decrease between successive iterations. Besides, one need not to decide how to update the penalty parameter. This approach resembles the filter method introduced by Fletcher and Leyffer [Math. Program., 91 (2001), pp. 239-269], but it is less tolerant since a merit function is still used. Numerical comparison with standard methods shows that this strategy is promising.
publishDate 2007
dc.date.none.fl_str_mv 2007-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
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status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1807-03022007000300003
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1807-03022007000300003
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S0101-82052007000300003
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.26 n.3 2007
reponame:Computational & Applied Mathematics
instname:Sociedade Brasileira de Matemática Aplicada e Computacional (SBMAC)
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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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