Loraine - An interior-point solver for low-rank semidefinite programming
Résumé
The aim of this paper is to introduce a new code for the solution of large-and-sparse linear Semidefinite Programs (SDPs) with low-rank solutions and/or low-rank data. We propose to use a preconditioned conjugate gradient method within an interior-point SDP algorithm and an efficient preconditioner fully utilizing the low-rank information. The efficiency is demonstrated by numerical experiments using the truss topology optimization problems, Lasserre relaxations of the MAXCUT problems and the sensor network localization problems.
Mots clés
Semidefinite optimization interior-point methods preconditioned conjugate gradients truss topology optimization MAXCUT problem Lasserre relaxations sensor network localization AMS CLASSIFICATION 90C22 90C51 65F08 74P05
Semidefinite optimization
interior-point methods
preconditioned conjugate gradients
truss topology optimization
MAXCUT problem
Lasserre relaxations
sensor network localization AMS CLASSIFICATION 90C22
90C51
65F08
74P05
Domaines
Mathématiques [math]Origine | Fichiers produits par l'(les) auteur(s) |
---|