PENNON. A generalized augmented Lagrangian method for semidefinite programming

0411229 - UTIA-B 20030216 RIV NL eng C - Conference Paper (international conference)
Kočvara, Michal - Stingl, M.
PENNON. A generalized augmented Lagrangian method for semidefinite programming.
Dordrecht: Kluwer, 2003. ISBN 1-4020-7532-4. In: High Performance Algorithms and Software for Nonlinear Optimization. - (di Pillo, G.; Murli, A.), s. 297-315
[High Performance Algorithms and Software for Nonlinear Optimization. Erice (IT), 30.06.2001-08.07.2001]
R&D Projects: GA ČR GA201/00/0080
Grant - others:BMBF(DE) 03ZOM3ER
Institutional research plan: CEZ:AV0Z1075907
Keywords : semidefinite programming * cone programming * method of augmented Langrangians
Subject RIV: BA - General Mathematics

This article describes a generalization of the PBM method by Ben-Tal and Zibulevsky to convex semidefinite programming problems. The algorithm used is a generalized version of the Augmented Lagrangian method. We present details of this algorithm as implemented in a new code PENNON. The code can also solve second-order conic programming (SOCP) problems, as well as problems with a mixture of SDP, SOCP and NLP constraints. Results of extensive numerical tests are presented.
Permanent Link: http://hdl.handle.net/11104/0131315