Stabilized sequential quadratic programming for optimization and a stabilized Newton-type method for variational problems

dc.creatorFernandez, D
dc.creatorSolodov, M
dc.date2010
dc.dateSEP
dc.date2014-11-14T05:31:25Z
dc.date2015-11-26T16:04:33Z
dc.date2014-11-14T05:31:25Z
dc.date2015-11-26T16:04:33Z
dc.date.accessioned2018-03-28T22:53:39Z
dc.date.available2018-03-28T22:53:39Z
dc.identifierMathematical Programming. Springer, v. 125, n. 1, n. 47, n. 73, 2010.
dc.identifier0025-5610
dc.identifierWOS:000281761500003
dc.identifier10.1007/s10107-008-0255-4
dc.identifierhttp://www.repositorio.unicamp.br/jspui/handle/REPOSIP/74517
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/74517
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/74517
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1265514
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionThe stabilized version of the sequential quadratic programming algorithm (sSQP) had been developed in order to achieve fast convergence despite possible degeneracy of constraints of optimization problems, when the Lagrange multipliers associated to a solution are not unique. Superlinear convergence of sSQP had been previously established under the strong second-order sufficient condition for optimality (without any constraint qualification assumptions). We prove a stronger superlinear convergence result than the above, assuming the usual second-order sufficient condition only. In addition, our analysis is carried out in the more general setting of variational problems, for which we introduce a natural extension of sSQP techniques. In the process, we also obtain a new error bound for Karush-Kuhn-Tucker systems for variational problems that holds under an appropriate second-order condition.
dc.description125
dc.description1
dc.description47
dc.description73
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionPRONEX-Optimization
dc.descriptionFundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ)
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionCNPq [301508/2005-4, 471267/2007-4]
dc.descriptionFAPERJ [E-26/151.942/2004]
dc.languageen
dc.publisherSpringer
dc.publisherNew York
dc.publisherEUA
dc.relationMathematical Programming
dc.relationMath. Program.
dc.rightsfechado
dc.rightshttp://www.springer.com/open+access/authors+rights?SGWID=0-176704-12-683201-0
dc.sourceWeb of Science
dc.subjectStabilized sequential quadratic programming
dc.subjectKarush-Kuhn-Tucker system
dc.subjectVariational inequality
dc.subjectNewton methods
dc.subjectSuperlinear convergence
dc.subjectError bound
dc.subjectError-bounds
dc.subjectDegenerate
dc.subjectIdentification
dc.subjectConvergence
dc.subjectAlgorithm
dc.subjectSqp
dc.titleStabilized sequential quadratic programming for optimization and a stabilized Newton-type method for variational problems
dc.typeArtículos de revistas


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