Local Convergence of the Affine-Scaling Interior-Point Algorithm for Nonlinear Programming

Detalhes bibliográficos
Autor(a) principal: Vicente, L. N.
Data de Publicação: 2000
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
DOI: 10.1023/A:1008774924658
Texto Completo: http://hdl.handle.net/10316/7756
https://doi.org/10.1023/A:1008774924658
Resumo: This paper addresses the local convergence properties of the affine-scaling interior-point algorithm for nonlinear programming. The analysis of local convergence is developed in terms of parameters that control the interior-point scheme and the size of the residual of the linear system that provides the step direction. The analysis follows the classical theory for quasi-Newton methods and addresses q-linear, q-superlinear, and q-quadratic rates of convergence.
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spelling Local Convergence of the Affine-Scaling Interior-Point Algorithm for Nonlinear ProgrammingThis paper addresses the local convergence properties of the affine-scaling interior-point algorithm for nonlinear programming. The analysis of local convergence is developed in terms of parameters that control the interior-point scheme and the size of the residual of the linear system that provides the step direction. The analysis follows the classical theory for quasi-Newton methods and addresses q-linear, q-superlinear, and q-quadratic rates of convergence.2000info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10316/7756http://hdl.handle.net/10316/7756https://doi.org/10.1023/A:1008774924658engComputational Optimization and Applications. 17:1 (2000) 23-35Vicente, L. N.info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2021-11-09T10:28:19Zoai:estudogeral.uc.pt:10316/7756Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T21:00:45.255700Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Local Convergence of the Affine-Scaling Interior-Point Algorithm for Nonlinear Programming
title Local Convergence of the Affine-Scaling Interior-Point Algorithm for Nonlinear Programming
spellingShingle Local Convergence of the Affine-Scaling Interior-Point Algorithm for Nonlinear Programming
Local Convergence of the Affine-Scaling Interior-Point Algorithm for Nonlinear Programming
Vicente, L. N.
Vicente, L. N.
title_short Local Convergence of the Affine-Scaling Interior-Point Algorithm for Nonlinear Programming
title_full Local Convergence of the Affine-Scaling Interior-Point Algorithm for Nonlinear Programming
title_fullStr Local Convergence of the Affine-Scaling Interior-Point Algorithm for Nonlinear Programming
Local Convergence of the Affine-Scaling Interior-Point Algorithm for Nonlinear Programming
title_full_unstemmed Local Convergence of the Affine-Scaling Interior-Point Algorithm for Nonlinear Programming
Local Convergence of the Affine-Scaling Interior-Point Algorithm for Nonlinear Programming
title_sort Local Convergence of the Affine-Scaling Interior-Point Algorithm for Nonlinear Programming
author Vicente, L. N.
author_facet Vicente, L. N.
Vicente, L. N.
author_role author
dc.contributor.author.fl_str_mv Vicente, L. N.
description This paper addresses the local convergence properties of the affine-scaling interior-point algorithm for nonlinear programming. The analysis of local convergence is developed in terms of parameters that control the interior-point scheme and the size of the residual of the linear system that provides the step direction. The analysis follows the classical theory for quasi-Newton methods and addresses q-linear, q-superlinear, and q-quadratic rates of convergence.
publishDate 2000
dc.date.none.fl_str_mv 2000
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10316/7756
http://hdl.handle.net/10316/7756
https://doi.org/10.1023/A:1008774924658
url http://hdl.handle.net/10316/7756
https://doi.org/10.1023/A:1008774924658
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Computational Optimization and Applications. 17:1 (2000) 23-35
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dc.identifier.doi.none.fl_str_mv 10.1023/A:1008774924658