Approximating Hessians in unconstrained optimization arising from discretized problems

V. Malmedy; Philippe Toint

doi:10.1007/s10589-010-9317-7

Approximating Hessians in unconstrained optimization arising from discretized problems

V. Malmedy, Philippe Toint

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Résumé

We consider Hessian approximation schemes for large-scale unconstrained optimization in the context of discretized problems. The considered Hessians typically present a nontrivial sparsity and partial separability structure. This allows iterative quasi-Newton methods to solve them despite of their size. Structured finite-difference methods and updating schemes based on the secant equation are presented and compared numerically inside the multilevel trust-region algorithm proposed by Gratton et al. (IMA J. Numer. Anal. 28(4):827-861, 2008).

langue originale	Anglais
Pages (de - à)	1-22
Nombre de pages	22
journal	Computational Optimization and Applications
Volume	50
Numéro de publication	1
Les DOIs	https://doi.org/10.1007/s10589-010-9317-7
Etat de la publication	Publié - 1 sept. 2011

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10.1007/s10589-010-9317-7

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1 Citations
1 Article

Quasi-Newton updates with weighted secant equations
Gratton, S., Malmedy, V. & Toint, P., 4 juil. 2015, Dans: Optimization Methods and Software. 30, 4, p. 748-755 8 p.
Résultats de recherche: Contribution à un journal/une revue › Article › Revue par des pairs

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ADALGOPT: ADALGOPT - Algorithmes avancés en optimisation non-linéaire
Sartenaer, A. & TOINT, P.
1/01/87 → …
Projet: Axe de recherche
Optimisation multi-échelle non-linéaire
Sartenaer, A., TOINT, P., Malmedy, V., Tomanos, D. & Weber Mendonca, M.
1/07/04 → 31/07/11
Projet: Recherche

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Approximating Hessians in unconstrained optimization arising from discretized problems

Résumé

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Autres fichiers et liens

Empreinte digitale

Résultat de recherche

Quasi-Newton updates with weighted secant equations

Projets

ADALGOPT: ADALGOPT - Algorithmes avancés en optimisation non-linéaire

Optimisation multi-échelle non-linéaire

Contient cette citation