On Convex Functions and the Finite Element Method

Autores
Aguilera, Néstor Edgardo; Morin, Pedro
Año de publicación
2009
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Many problems of theoretical and practical interest involve finding a convex or concave function.For instance, optimization problems such as finding the projection on the convex functions in $H^k(Omega)$, or some problems in economics.In the continuous setting and assuming smoothness, the convexity constraints may be given locally by asking the Hessian matrix to be positive semidefinite, but in making discrete approximations two difficulties arise: the continuous solutions may be not smooth, and an adequate discrete version of the Hessian must be given.In this paper we propose a finite element description of the Hessian, and prove convergence under very general conditions, even when the continuous solution is not smooth, working on any dimension, and requiring a linear number of constraints in the number of nodes.Using semidefinite programming codes, we show concrete examples of approximations to optimization problems.
Fil: Aguilera, Néstor Edgardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Matemática Aplicada del Litoral. Universidad Nacional del Litoral. Instituto de Matemática Aplicada del Litoral; Argentina
Fil: Morin, Pedro. Universidad Nacional del Litoral; Argentina
Materia
Finite Element Method
Optimization Problems
Convex Functions
Adaptive Meshes
Finite Element Method
Optimization Problems
Convex Functions
Adaptive Meshes
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/84278

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spelling On Convex Functions and the Finite Element MethodAguilera, Néstor EdgardoMorin, PedroFinite Element MethodOptimization ProblemsConvex FunctionsAdaptive MeshesFinite Element MethodOptimization ProblemsConvex FunctionsAdaptive Mesheshttps://purl.org/becyt/ford/1.1https://purl.org/becyt/ford/1Many problems of theoretical and practical interest involve finding a convex or concave function.For instance, optimization problems such as finding the projection on the convex functions in $H^k(Omega)$, or some problems in economics.In the continuous setting and assuming smoothness, the convexity constraints may be given locally by asking the Hessian matrix to be positive semidefinite, but in making discrete approximations two difficulties arise: the continuous solutions may be not smooth, and an adequate discrete version of the Hessian must be given.In this paper we propose a finite element description of the Hessian, and prove convergence under very general conditions, even when the continuous solution is not smooth, working on any dimension, and requiring a linear number of constraints in the number of nodes.Using semidefinite programming codes, we show concrete examples of approximations to optimization problems.Fil: Aguilera, Néstor Edgardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Matemática Aplicada del Litoral. Universidad Nacional del Litoral. Instituto de Matemática Aplicada del Litoral; ArgentinaFil: Morin, Pedro. Universidad Nacional del Litoral; ArgentinaSociety for Industrial and Applied Mathematics2009-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/84278Aguilera, Néstor Edgardo; Morin, Pedro; On Convex Functions and the Finite Element Method; Society for Industrial and Applied Mathematics; Siam Journal On Numerical Analysis; 47; 4; 12-2009; 3139-31570036-1429CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1137/080720917info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:59:46Zoai:ri.conicet.gov.ar:11336/84278instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 09:59:47.245CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv On Convex Functions and the Finite Element Method
title On Convex Functions and the Finite Element Method
spellingShingle On Convex Functions and the Finite Element Method
Aguilera, Néstor Edgardo
Finite Element Method
Optimization Problems
Convex Functions
Adaptive Meshes
Finite Element Method
Optimization Problems
Convex Functions
Adaptive Meshes
title_short On Convex Functions and the Finite Element Method
title_full On Convex Functions and the Finite Element Method
title_fullStr On Convex Functions and the Finite Element Method
title_full_unstemmed On Convex Functions and the Finite Element Method
title_sort On Convex Functions and the Finite Element Method
dc.creator.none.fl_str_mv Aguilera, Néstor Edgardo
Morin, Pedro
author Aguilera, Néstor Edgardo
author_facet Aguilera, Néstor Edgardo
Morin, Pedro
author_role author
author2 Morin, Pedro
author2_role author
dc.subject.none.fl_str_mv Finite Element Method
Optimization Problems
Convex Functions
Adaptive Meshes
Finite Element Method
Optimization Problems
Convex Functions
Adaptive Meshes
topic Finite Element Method
Optimization Problems
Convex Functions
Adaptive Meshes
Finite Element Method
Optimization Problems
Convex Functions
Adaptive Meshes
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.1
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Many problems of theoretical and practical interest involve finding a convex or concave function.For instance, optimization problems such as finding the projection on the convex functions in $H^k(Omega)$, or some problems in economics.In the continuous setting and assuming smoothness, the convexity constraints may be given locally by asking the Hessian matrix to be positive semidefinite, but in making discrete approximations two difficulties arise: the continuous solutions may be not smooth, and an adequate discrete version of the Hessian must be given.In this paper we propose a finite element description of the Hessian, and prove convergence under very general conditions, even when the continuous solution is not smooth, working on any dimension, and requiring a linear number of constraints in the number of nodes.Using semidefinite programming codes, we show concrete examples of approximations to optimization problems.
Fil: Aguilera, Néstor Edgardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Matemática Aplicada del Litoral. Universidad Nacional del Litoral. Instituto de Matemática Aplicada del Litoral; Argentina
Fil: Morin, Pedro. Universidad Nacional del Litoral; Argentina
description Many problems of theoretical and practical interest involve finding a convex or concave function.For instance, optimization problems such as finding the projection on the convex functions in $H^k(Omega)$, or some problems in economics.In the continuous setting and assuming smoothness, the convexity constraints may be given locally by asking the Hessian matrix to be positive semidefinite, but in making discrete approximations two difficulties arise: the continuous solutions may be not smooth, and an adequate discrete version of the Hessian must be given.In this paper we propose a finite element description of the Hessian, and prove convergence under very general conditions, even when the continuous solution is not smooth, working on any dimension, and requiring a linear number of constraints in the number of nodes.Using semidefinite programming codes, we show concrete examples of approximations to optimization problems.
publishDate 2009
dc.date.none.fl_str_mv 2009-12
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
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://hdl.handle.net/11336/84278
Aguilera, Néstor Edgardo; Morin, Pedro; On Convex Functions and the Finite Element Method; Society for Industrial and Applied Mathematics; Siam Journal On Numerical Analysis; 47; 4; 12-2009; 3139-3157
0036-1429
CONICET Digital
CONICET
url http://hdl.handle.net/11336/84278
identifier_str_mv Aguilera, Néstor Edgardo; Morin, Pedro; On Convex Functions and the Finite Element Method; Society for Industrial and Applied Mathematics; Siam Journal On Numerical Analysis; 47; 4; 12-2009; 3139-3157
0036-1429
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1137/080720917
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Society for Industrial and Applied Mathematics
publisher.none.fl_str_mv Society for Industrial and Applied Mathematics
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.13397