Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/348191
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dc.contributor.CRUESPUNIVERSIDADE ESTADUAL DE CAMPINASpt_BR
dc.contributor.authorunicampAndreani, Roberto-
dc.typeArtigopt_BR
dc.titleTwo new weak constraint qualifications and applicationspt_BR
dc.contributor.authorAndreani, Roberto-
dc.contributor.authorHaeser, Gabriel-
dc.contributor.authorSchuverdt, María Laura-
dc.contributor.authorSilva, Paulo J. S.-
dc.subjectCondições de qualificaçãopt_BR
dc.subject.otherlanguageConstraint qualificationspt_BR
dc.description.abstractWe present two new constraint qualifications (CQs) that are weaker than the recently introduced relaxed constant positive linear dependence (RCPLD) CQ. RCPLD is based on the assumption that many subsets of the gradients of the active constraints preserve positive linear dependence locally. A major open question was to identify the exact set of gradients whose properties had to be preserved locally and that would still work as a CQ. This is done in the first new CQ, which we call the constant rank of the subspace component (CRSC) CQ. This new CQ also preserves many of the good properties of RCPLD, such as local stability and the validity of an error bound. We also introduce an even weaker CQ, called the constant positive generator (CPG), which can replace RCPLD in the analysis of the global convergence of algorithms. We close this work by extending convergence results of algorithms belonging to all the main classes of nonlinear optimization methods: sequential quadratic programming, augmented Lagrangians, interior point algorithms, and inexact restorationpt_BR
dc.relation.ispartofSIAM journal on optimizationpt_BR
dc.relation.ispartofabbreviationSIAM j. optim.pt_BR
dc.publisher.cityPhiladelphia, PApt_BR
dc.publisher.countryEstados Unidospt_BR
dc.publisherSociety for Industrial and Applied Mathematicspt_BR
dc.date.issued2012-
dc.date.monthofcirculationSept.pt_BR
dc.language.isoengpt_BR
dc.description.volume22pt_BR
dc.description.issuenumber3pt_BR
dc.description.firstpage1109pt_BR
dc.description.lastpage113pt_BR
dc.rightsFechadopt_BR
dc.sourceWOSpt_BR
dc.identifier.issn1052-6234pt_BR
dc.identifier.eissn1095-7189pt_BR
dc.identifier.doi10.1137/110843939pt_BR
dc.identifier.urlhttps://epubs.siam.org/doi/10.1137/110843939pt_BR
dc.description.sponsorshipFUNDAÇÃO CARLOS CHAGAS FILHO DE AMPARO À PESQUISA DO ESTADO DO RIO DE JANEIRO - FAPERJpt_BR
dc.description.sponsorshipCONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQpt_BR
dc.description.sponsorshipFUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESPpt_BR
dc.description.sponsordocumentnumberE-26/171.510/2006-APQ1; 300900/2009-0; 303030/2007-0; 305740/2010-5; 474138/2008-9pt_BR
dc.description.sponsordocumentnumberE-26/171.510/2006-APQ1pt_BR
dc.description.sponsordocumentnumber2006/53768-0; 2009/09414-7; 2010/19720-5pt_BR
dc.date.available2020-08-27T23:58:58Z-
dc.date.accessioned2020-08-27T23:58:58Z-
dc.description.provenanceSubmitted by Thais de Brito Barroso (tbrito@unicamp.br) on 2020-08-27T23:58:58Z No. of bitstreams: 0. Added 1 bitstream(s) on 2021-01-04T15:14:28Z : No. of bitstreams: 1 000310214800019.pdf: 463288 bytes, checksum: c5b9534d1c2f726478bac4e9f5ea3dad (MD5)en
dc.description.provenanceMade available in DSpace on 2020-08-27T23:58:58Z (GMT). No. of bitstreams: 0 Previous issue date: 2012en
dc.identifier.urihttp://repositorio.unicamp.br/jspui/handle/REPOSIP/348191-
dc.contributor.departmentDepartamento de Matemática Aplicadapt_BR
dc.contributor.unidadeInstituto de Matemática, Estatística e Computação Científicapt_BR
dc.subject.keywordError boundpt_BR
dc.subject.keywordAlgorithmic convergencept_BR
dc.identifier.source000310214800019pt_BR
dc.creator.orcid0000-0003-2031-4325pt_BR
dc.type.formArtigopt_BR
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