Cutting planes and a biased Newton direction for minimizing quasiconvex functions

Autores
Echebest, Nélida Ester; Guardarucci, María Teresa; Scolnik, Hugo Daniel; Vacchino, María Cristina
Año de publicación
2000
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
A biased Newton direction is introduced for minimizing quasiconver functions with bounded level sets. It is a generalization of the usual Newton’s direction for strictly convex quadratic functions. This new direction can be derived from the intersection of approzimating hyperplanes to the epigraph at points on the boundary of the same level set. Based on that direction, an unconstrained minimization algorithm is presented. It is proved to have global and local-quadratic convergence under standard hypotheses. These theoretical results may lead to different methods based on computing search directions using only first order information at points on the level sets. Most of all if the computational cost can be reduced by relaxing some of the conditions according for instance to the results presented in the Appendix. Some tests are presented to show the qualitative behavior of the new direction and with the purpose to stimulate further research on these kind of algorithms.
Facultad de Ciencias Exactas
Materia
Matemática
Quasiconvex functions
Level sets
Discretization methods
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/150086

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spelling Cutting planes and a biased Newton direction for minimizing quasiconvex functionsEchebest, Nélida EsterGuardarucci, María TeresaScolnik, Hugo DanielVacchino, María CristinaMatemáticaQuasiconvex functionsLevel setsDiscretization methodsA biased Newton direction is introduced for minimizing quasiconver functions with bounded level sets. It is a generalization of the usual Newton’s direction for strictly convex quadratic functions. This new direction can be derived from the intersection of approzimating hyperplanes to the epigraph at points on the boundary of the same level set. Based on that direction, an unconstrained minimization algorithm is presented. It is proved to have global and local-quadratic convergence under standard hypotheses. These theoretical results may lead to different methods based on computing search directions using only first order information at points on the level sets. Most of all if the computational cost can be reduced by relaxing some of the conditions according for instance to the results presented in the Appendix. Some tests are presented to show the qualitative behavior of the new direction and with the purpose to stimulate further research on these kind of algorithms.Facultad de Ciencias Exactas2000info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf135-166http://sedici.unlp.edu.ar/handle/10915/150086enginfo:eu-repo/semantics/altIdentifier/issn/1014-8264info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-03T11:10:35Zoai:sedici.unlp.edu.ar:10915/150086Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-03 11:10:35.365SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Cutting planes and a biased Newton direction for minimizing quasiconvex functions
title Cutting planes and a biased Newton direction for minimizing quasiconvex functions
spellingShingle Cutting planes and a biased Newton direction for minimizing quasiconvex functions
Echebest, Nélida Ester
Matemática
Quasiconvex functions
Level sets
Discretization methods
title_short Cutting planes and a biased Newton direction for minimizing quasiconvex functions
title_full Cutting planes and a biased Newton direction for minimizing quasiconvex functions
title_fullStr Cutting planes and a biased Newton direction for minimizing quasiconvex functions
title_full_unstemmed Cutting planes and a biased Newton direction for minimizing quasiconvex functions
title_sort Cutting planes and a biased Newton direction for minimizing quasiconvex functions
dc.creator.none.fl_str_mv Echebest, Nélida Ester
Guardarucci, María Teresa
Scolnik, Hugo Daniel
Vacchino, María Cristina
author Echebest, Nélida Ester
author_facet Echebest, Nélida Ester
Guardarucci, María Teresa
Scolnik, Hugo Daniel
Vacchino, María Cristina
author_role author
author2 Guardarucci, María Teresa
Scolnik, Hugo Daniel
Vacchino, María Cristina
author2_role author
author
author
dc.subject.none.fl_str_mv Matemática
Quasiconvex functions
Level sets
Discretization methods
topic Matemática
Quasiconvex functions
Level sets
Discretization methods
dc.description.none.fl_txt_mv A biased Newton direction is introduced for minimizing quasiconver functions with bounded level sets. It is a generalization of the usual Newton’s direction for strictly convex quadratic functions. This new direction can be derived from the intersection of approzimating hyperplanes to the epigraph at points on the boundary of the same level set. Based on that direction, an unconstrained minimization algorithm is presented. It is proved to have global and local-quadratic convergence under standard hypotheses. These theoretical results may lead to different methods based on computing search directions using only first order information at points on the level sets. Most of all if the computational cost can be reduced by relaxing some of the conditions according for instance to the results presented in the Appendix. Some tests are presented to show the qualitative behavior of the new direction and with the purpose to stimulate further research on these kind of algorithms.
Facultad de Ciencias Exactas
description A biased Newton direction is introduced for minimizing quasiconver functions with bounded level sets. It is a generalization of the usual Newton’s direction for strictly convex quadratic functions. This new direction can be derived from the intersection of approzimating hyperplanes to the epigraph at points on the boundary of the same level set. Based on that direction, an unconstrained minimization algorithm is presented. It is proved to have global and local-quadratic convergence under standard hypotheses. These theoretical results may lead to different methods based on computing search directions using only first order information at points on the level sets. Most of all if the computational cost can be reduced by relaxing some of the conditions according for instance to the results presented in the Appendix. Some tests are presented to show the qualitative behavior of the new direction and with the purpose to stimulate further research on these kind of algorithms.
publishDate 2000
dc.date.none.fl_str_mv 2000
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Articulo
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/150086
url http://sedici.unlp.edu.ar/handle/10915/150086
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/issn/1014-8264
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
135-166
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instname_str Universidad Nacional de La Plata
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repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
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