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Résumé
We consider the global and local convergence properties of a class of augmented Lagrangian methods for solving nonlinear programming problems. In these methods, linear and more general constraints are handled in different ways. The general constraints are combined with the objective function in an augmented Lagrangian. The iteration consists of solving a sequence of subproblems; in each subproblem the augmented Lagrangian is approximately minimized in the region denned by the linear constraints. A subproblem is terminated as soon as a stopping condition is satisfied. The stopping rules that we consider here encompass practical tests used in several existing packages for linearly constrained optimization. Our algorithm also allows different penalty parameters to be associated with disjoint subsets of the general constraints. In this paper, we analyze the convergence of the sequence of iterates generated by such an algorithm and prove global and fast linear convergence as well as show that potentially troublesome penalty parameters remain bounded away from zero.
langue originale  Anglais 

Pages (de  à)  674703 
Nombre de pages  30 
journal  SIAM Journal on Optimization 
Volume  6 
Numéro de publication  3 
Etat de la publication  Publié  1 août 1996 
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Projets

ADALGOPT: ADALGOPT  Algorithmes avancés en optimisation nonlinéaire
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
Thèses de l'étudiant

On some strategies for handling constraints in nonlinear optimization
Author: Sartenaer, A., 1991Superviseur: Toint, P. (Promoteur), Conn, A. (Personne externe) (Jury), Sachs, E. (Personne externe) (Jury), Nguyen, V. H. (Jury) & Strodiot, J. (Jury)
Thèse de l'étudiant: Doc types › Docteur en Sciences