An augmented Lagrangian method for equality constrained optimization with rapid infeasibility detection capabilities - Archive ouverte HAL Accéder directement au contenu
Rapport (Rapport De Recherche) Année : 2018

An augmented Lagrangian method for equality constrained optimization with rapid infeasibility detection capabilities

Résumé

We present a primal-dual augmented Lagrangian method for solving an equality constrained minimization problem, which is able to rapidly detect infeasibility. The method is based on a modification of the algorithm proposed in [1]. A new parameter is introduced to scale the objective function and, in case of infeasibility, to force the convergence of the iterates to an infea-sible stationary point. It is shown, under mild assumptions, that whenever the algorithm converges to an infeasible stationary point, the rate of convergence is quadratic. This is a new convergence result for the class of augmented La-grangian methods. The global convergence of the algorithm is also analysed. It is also proved that, when the algorithm converges to a stationary point, the properties of the original algorithm [1] are preserved. The numerical experiments show that our new approach is as good as the original one when the algorithm converges to a local minimum, but much more efficient in case of infeasibility.
Fichier principal
Vignette du fichier
ArmandTran2018a.pdf (668.24 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01785365 , version 1 (04-05-2018)

Identifiants

  • HAL Id : hal-01785365 , version 1

Citer

Paul Armand, Ngoc Nguyen Tran. An augmented Lagrangian method for equality constrained optimization with rapid infeasibility detection capabilities. [Research Report] Université de Limoges, France; XLIM. 2018. ⟨hal-01785365⟩
64 Consultations
844 Téléchargements

Partager

Gmail Facebook X LinkedIn More