A relaxed constant positive linear dependence constraint qualification and applications

dc.creatorAndreani, Roberto
dc.creatorHaeser, Gabriel
dc.creatorLaura Schuverdt, Maria
dc.creatorSilva, Paulo J. S.
dc.date2012
dc.date2013-09-19T18:06:43Z
dc.date2016-06-30T18:27:05Z
dc.date2013-09-19T18:06:43Z
dc.date2016-06-30T18:27:05Z
dc.date.accessioned2018-03-29T01:52:59Z
dc.date.available2018-03-29T01:52:59Z
dc.identifierMathematical Programming. Springer, v.135, n.41306, p.255-273, 2012
dc.identifier0025-5610
dc.identifierWOS:000308647100009
dc.identifier10.1007/s10107-011-0456-0
dc.identifierhttp://www.repositorio.unicamp.br/jspui/handle/REPOSIP/2384
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/2384
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1308294
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.descriptionIn this work we introduce a relaxed version of the constant positive linear dependence constraint qualification (CPLD) that we call RCPLD. This development is inspired by a recent generalization of the constant rank constraint qualification by Minchenko and Stakhovski that was called RCRCQ. We show that RCPLD is enough to ensure the convergence of an augmented Lagrangian algorithm and that it asserts the validity of an error bound. We also provide proofs and counter-examples that show the relations of RCRCQ and RCPLD with other known constraint qualifications. In particular, RCPLD is strictly weaker than CPLD and RCRCQ, while still stronger than Abadie's constraint qualification. We also verify that the second order necessary optimality condition holds under RCRCQ.
dc.description135
dc.description01/fev
dc.description255
dc.description273
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.languageeng
dc.publisherSpringer
dc.publisherNew York
dc.relationMathematical Programming
dc.rightsfechado
dc.sourceWOS
dc.subjectNonlinear programming
dc.subjectConstraint qualifications
dc.subjectAugmented Lagrangian
dc.subjectError bound property
dc.subjectAUGMENTED LAGRANGIAN-METHODS
dc.subjectLOWER-LEVEL CONSTRAINTS
dc.subjectOPTIMALITY
dc.titleA relaxed constant positive linear dependence constraint qualification and applications
dc.typeArtículos de revistas


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