Derivative-free methods for nonlinear programming with general lower-level constraints

Detalhes bibliográficos
Autor(a) principal: Diniz-Ehrhardt,M. A.
Data de Publicação: 2011
Outros Autores: Martínez,J. M., Pedroso,L. G.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Computational & Applied Mathematics
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1807-03022011000100003
Resumo: Augmented Lagrangian methods for derivative-free continuous optimization with constraints are introduced in this paper. The algorithms inherit the convergence results obtained by Andreani, Birgin, Martínez and Schuverdt for the case in which analytic derivatives exist and are available. In particular, feasible limit points satisfy KKT conditions under the Constant Positive Linear Dependence (CPLD) constraint qualification. The form of our main algorithm allows us to employ well established derivative-free subalgorithms for solving lower-level constrained subproblems. Numerical experiments are presented.
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spelling Derivative-free methods for nonlinear programming with general lower-level constraintsnonlinear programmingAugmented Lagrangianglobal convergenceoptimality conditionsderivative-free optimizationconstraint qualificationsAugmented Lagrangian methods for derivative-free continuous optimization with constraints are introduced in this paper. The algorithms inherit the convergence results obtained by Andreani, Birgin, Martínez and Schuverdt for the case in which analytic derivatives exist and are available. In particular, feasible limit points satisfy KKT conditions under the Constant Positive Linear Dependence (CPLD) constraint qualification. The form of our main algorithm allows us to employ well established derivative-free subalgorithms for solving lower-level constrained subproblems. Numerical experiments are presented.Sociedade Brasileira de Matemática Aplicada e Computacional2011-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1807-03022011000100003Computational & Applied Mathematics v.30 n.1 2011reponame:Computational & Applied Mathematicsinstname:Sociedade Brasileira de Matemática Aplicada e Computacional (SBMAC)instacron:SBMAC10.1590/S1807-03022011000100003info:eu-repo/semantics/openAccessDiniz-Ehrhardt,M. A.Martínez,J. M.Pedroso,L. G.eng2016-09-29T00:00:00Zoai:scielo:S1807-03022011000100003Revistahttps://www.scielo.br/j/cam/ONGhttps://old.scielo.br/oai/scielo-oai.php||sbmac@sbmac.org.br1807-03022238-3603opendoar:2016-09-29T00:00Computational & Applied Mathematics - Sociedade Brasileira de Matemática Aplicada e Computacional (SBMAC)false
dc.title.none.fl_str_mv Derivative-free methods for nonlinear programming with general lower-level constraints
title Derivative-free methods for nonlinear programming with general lower-level constraints
spellingShingle Derivative-free methods for nonlinear programming with general lower-level constraints
Diniz-Ehrhardt,M. A.
nonlinear programming
Augmented Lagrangian
global convergence
optimality conditions
derivative-free optimization
constraint qualifications
title_short Derivative-free methods for nonlinear programming with general lower-level constraints
title_full Derivative-free methods for nonlinear programming with general lower-level constraints
title_fullStr Derivative-free methods for nonlinear programming with general lower-level constraints
title_full_unstemmed Derivative-free methods for nonlinear programming with general lower-level constraints
title_sort Derivative-free methods for nonlinear programming with general lower-level constraints
author Diniz-Ehrhardt,M. A.
author_facet Diniz-Ehrhardt,M. A.
Martínez,J. M.
Pedroso,L. G.
author_role author
author2 Martínez,J. M.
Pedroso,L. G.
author2_role author
author
dc.contributor.author.fl_str_mv Diniz-Ehrhardt,M. A.
Martínez,J. M.
Pedroso,L. G.
dc.subject.por.fl_str_mv nonlinear programming
Augmented Lagrangian
global convergence
optimality conditions
derivative-free optimization
constraint qualifications
topic nonlinear programming
Augmented Lagrangian
global convergence
optimality conditions
derivative-free optimization
constraint qualifications
description Augmented Lagrangian methods for derivative-free continuous optimization with constraints are introduced in this paper. The algorithms inherit the convergence results obtained by Andreani, Birgin, Martínez and Schuverdt for the case in which analytic derivatives exist and are available. In particular, feasible limit points satisfy KKT conditions under the Constant Positive Linear Dependence (CPLD) constraint qualification. The form of our main algorithm allows us to employ well established derivative-free subalgorithms for solving lower-level constrained subproblems. Numerical experiments are presented.
publishDate 2011
dc.date.none.fl_str_mv 2011-01-01
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=S1807-03022011000100003
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1807-03022011000100003
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S1807-03022011000100003
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.30 n.1 2011
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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