A filter-trust-region method for unconstrained optimization

Nick Gould; Caroline Sainvitu; Philippe Toint

doi:10.1137/040603851

A filter-trust-region method for unconstrained optimization

Nick Gould, Caroline Sainvitu, Philippe Toint

Résultats de recherche: Contribution à un journal/une revue › Article › Revue par des pairs

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Résumé

A new filter-trust-region algorithm for solving unconstrained nonlinear optimization problems is introduced. Based on the filter technique introduced by Fletcher and Leyffer, it extends an existing technique of Gould, Leyffer, and Toint [SIAM J. Optim., 15 (2004), pp. 17-38] for nonlinear equations and nonlinear least-squares to the fully general unconstrained optimization problem. The new algorithm is shown to be globally convergent to at least one second-order critical point, and numerical experiments indicate that it is very competitive with more classical trust-region algorithms. © 2005 Society for Industrial and Applied Mathematics.

langue originale	Anglais
Pages (de - à)	341-357
Nombre de pages	17
journal	SIAM Journal on Optimization
Volume	16
Numéro de publication	2
Les DOIs	https://doi.org/10.1137/040603851
Etat de la publication	Publié - 1 janv. 2006

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10.1137/040603851

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Algorithmes de filtre pour les problèmes nonlinéaires
Toint, P. (Responsable du Projet) & SAINVITU, C. (Chercheur)
2/02/02 → 31/08/11
Projet: Recherche

Filter-trust-region methods for nonlinear optimization
Sainvitu, C. (Auteur), Toint, P. (Promoteur), Gould, N. I. M. (Jury), VICENTE, L. (Jury), Sartenaer, A. (Jury) & Strodiot, J.-J. (Jury), 17 avr. 2007
Student thesis: Doc types › Docteur en Sciences

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A filter-trust-region method for unconstrained optimization

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Algorithmes de filtre pour les problèmes nonlinéaires

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Filter-trust-region methods for nonlinear optimization

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