On the global convergence of interior-point nonlinear programming algorithms

dc.creatorHaeser, G
dc.date2010
dc.date2014-11-14T02:39:52Z
dc.date2015-11-26T17:12:47Z
dc.date2014-11-14T02:39:52Z
dc.date2015-11-26T17:12:47Z
dc.date.accessioned2018-03-29T00:01:11Z
dc.date.available2018-03-29T00:01:11Z
dc.identifierComputational & Applied Mathematics. Springer Heidelberg, v. 29, n. 2, n. 125, n. 138, 2010.
dc.identifier1807-0302
dc.identifierWOS:000280606800003
dc.identifierhttp://www.repositorio.unicamp.br/jspui/handle/REPOSIP/68676
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/68676
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/68676
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1281416
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.descriptionCaratheodory's lemma states that if we have a linear combination of vectors in R-n, we can rewrite this combination using a linearly independent subset. This lemma has been successfully applied in nonlinear optimization in many contexts. In this work we present a new version of this celebrated result, in which we obtained new bounds for the size of the coefficients in the linear combination and we provide examples where these bounds are useful. We show how these new bounds can be used to prove that the internal penalty method converges to KKT points, and we prove that the hypothesis to obtain this result cannot be weakened. The new bounds also provides us some new results of convergence for the quasi feasible interior point l(2)-penalty method of Chen and Goldfarb [7].
dc.description29
dc.description2
dc.description125
dc.description138
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.descriptionFAPESP [05/02163-8]
dc.languageen
dc.publisherSpringer Heidelberg
dc.publisherHeidelberg
dc.publisherAlemanha
dc.relationComputational & Applied Mathematics
dc.relationComput. Appl. Math.
dc.rightsaberto
dc.rightshttp://www.springer.com/open+access/authors+rights?SGWID=0-176704-12-683201-0
dc.sourceWeb of Science
dc.subjectnonlinear programming
dc.subjectconstraint qualifications
dc.subjectinterior point methods
dc.subjectAugmented Lagrangian-methods
dc.subjectLinear-dependence Condition
dc.subjectConstraint Qualification
dc.subjectOptimality
dc.titleOn the global convergence of interior-point nonlinear programming algorithms
dc.typeArtículos de revistas


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