Sensitivity of trust-region algorithms to their parameters

Nick Gould; D. Orban; A. Sartenaer; Philippe Toint

doi:10.1007/s10288-005-0065-y

Sensitivity of trust-region algorithms to their parameters

Nick Gould, D. Orban, A. Sartenaer, Philippe Toint

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Résumé

In this paper, we examine the sensitivity of trust-region algorithms on the parameters related to the step acceptance and update of the trust region. We show, in the context of unconstrained programming, that the numerical efficiency of these algorithms can easily be improved by choosing appropriate parameters. Recommended ranges of values for these parameters are exhibited on the basis of extensive numerical tests. © Springer-Verlag 2005.

langue originale	Anglais
Pages (de - à)	227-241
Nombre de pages	15
journal	4OR
Volume	3
Numéro de publication	3
Les DOIs	https://doi.org/10.1007/s10288-005-0065-y
Etat de la publication	Publié - 1 sept. 2005

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10.1007/s10288-005-0065-y

52248Accepted author manuscript, 410 KB

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1 Terminé
1 Actif

ADALGOPT: ADALGOPT - Algorithmes avancés en optimisation non-linéaire
Sartenaer, A. & TOINT, P.
1/01/87 → …
Projet: Axe de recherche
Détermination de paramètres optimaux dans les méthodes de région de confiance en optimisation non-linéaire
Sartenaer, A. & TOINT, P.
1/09/97 → 1/02/05
Projet: Recherche

Contient cette citation

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abstract = "In this paper, we examine the sensitivity of trust-region algorithms on the parameters related to the step acceptance and update of the trust region. We show, in the context of unconstrained programming, that the numerical efficiency of these algorithms can easily be improved by choosing appropriate parameters. Recommended ranges of values for these parameters are exhibited on the basis of extensive numerical tests. {\textcopyright} Springer-Verlag 2005.",

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AB - In this paper, we examine the sensitivity of trust-region algorithms on the parameters related to the step acceptance and update of the trust region. We show, in the context of unconstrained programming, that the numerical efficiency of these algorithms can easily be improved by choosing appropriate parameters. Recommended ranges of values for these parameters are exhibited on the basis of extensive numerical tests. © Springer-Verlag 2005.

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Sensitivity of trust-region algorithms to their parameters

Résumé

Accès au document

Autres fichiers et liens

Empreinte digitale

Projets

ADALGOPT: ADALGOPT - Algorithmes avancés en optimisation non-linéaire

Détermination de paramètres optimaux dans les méthodes de région de confiance en optimisation non-linéaire

Contient cette citation