Global convergence of a class of trust region algorithms for optimization with simple bounds

Andy Conn; Nick Gould; Philippe Toint

Global convergence of a class of trust region algorithms for optimization with simple bounds

Andy Conn, Nick Gould, Philippe Toint

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

Résumé

This paper extends the known excellent global convergence properties of trust-region algorithms for unconstrained optimization to the case where bounds on the variables are present. Weak conditions on the accuracy of the Hessian approximations are considered. It is also shown that, when the strict complementarity condition holds, the proposed algorithms reduce to an unconstrained calculation after finitely many iterations, allowing a fast rate of convergence.

langue originale	Anglais
Pages (de - à)	430-460
Nombre de pages	31
journal	SIAM Journal on Numerical Analysis
Volume	25
Numéro de publication	182
Etat de la publication	Publié - 1988

1 Terminé
1 Actif

ADALGOPT: ADALGOPT - Algorithmes avancés en optimisation non-linéaire
Sartenaer, A. & TOINT, P.
1/01/87 → …
Projet: Axe de recherche
LANCELOT: LANCELOT, un logiciel pour l'optimisation non linéaire de grande taille
TOINT, P., Sartenaer, A., Gould, N. I. M. & Conn, A.
1/09/87 → 1/09/00
Projet: Recherche

Contient cette citation

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title = "Global convergence of a class of trust region algorithms for optimization with simple bounds",

abstract = "This paper extends the known excellent global convergence properties of trust-region algorithms for unconstrained optimization to the case where bounds on the variables are present. Weak conditions on the accuracy of the Hessian approximations are considered. It is also shown that, when the strict complementarity condition holds, the proposed algorithms reduce to an unconstrained calculation after finitely many iterations, allowing a fast rate of convergence.",

author = "Andy Conn and Nick Gould and Philippe Toint",

year = "1988",

language = "English",

volume = "25",

pages = "430--460",

journal = "SIAM Journal on Numerical Analysis",

issn = "0036-1429",

publisher = "Society for Industrial and Applied Mathematics Publications",

number = "182",

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T1 - Global convergence of a class of trust region algorithms for optimization with simple bounds

AU - Conn, Andy

AU - Gould, Nick

AU - Toint, Philippe

PY - 1988

Y1 - 1988

N2 - This paper extends the known excellent global convergence properties of trust-region algorithms for unconstrained optimization to the case where bounds on the variables are present. Weak conditions on the accuracy of the Hessian approximations are considered. It is also shown that, when the strict complementarity condition holds, the proposed algorithms reduce to an unconstrained calculation after finitely many iterations, allowing a fast rate of convergence.

AB - This paper extends the known excellent global convergence properties of trust-region algorithms for unconstrained optimization to the case where bounds on the variables are present. Weak conditions on the accuracy of the Hessian approximations are considered. It is also shown that, when the strict complementarity condition holds, the proposed algorithms reduce to an unconstrained calculation after finitely many iterations, allowing a fast rate of convergence.

M3 - Article

SN - 0036-1429

VL - 25

SP - 430

EP - 460

JO - SIAM Journal on Numerical Analysis

JF - SIAM Journal on Numerical Analysis

IS - 182

ER -

Global convergence of a class of trust region algorithms for optimization with simple bounds

Résumé

Empreinte digitale

Projets

ADALGOPT: ADALGOPT - Algorithmes avancés en optimisation non-linéaire

LANCELOT: LANCELOT, un logiciel pour l'optimisation non linéaire de grande taille

Contient cette citation