Using a Factored Dual in Augmented Lagrangian Methods for Semidefinite Programming

Autor:	De Santis, Marianna, Rendl, Franz, Wiegele, Angelika
Rok vydání:	2017
Předmět:	Mathematics - Optimization and Control
Zdroj:	Operations Research Letters, Volume 46, Issue 5, Pages 523-528, 2018
Druh dokumentu:	Working Paper
DOI:	10.1016/j.orl.2018.08.003
Popis:	In the context of augmented Lagrangian approaches for solving semidefinite programming problems, we investigate the possibility of eliminating the positive semidefinite constraint on the dual matrix by employing a factorization. Hints on how to deal with the resulting unconstrained maximization of the augmented Lagrangian are given. We further use the approximate maximum of the augmented Lagrangian with the aim of improving the convergence rate of alternating direction augmented Lagrangian frameworks. Numerical results are reported, showing the benefits of the approach. Comment: 7 pages
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1710.04869 Zobrazit plný text záznamu View this record from Arxiv