PENNON. A generalized augmented Lagrangian method for semidefinite programming

Number of the records: 1

1.

SYSNO ASEP	0411229
Document Type	C - Proceedings Paper (int. conf.)
R&D Document Type	Conference Paper
Title	PENNON. A generalized augmented Lagrangian method for semidefinite programming
Author(s)	Kočvara, Michal (UTIA-B)_{RID, ORCID} Stingl, M. (DE)
Issue data	Dordrecht: Kluwer, 2003
ISBN	1-4020-7532-4
Source Title	High Performance Algorithms and Software for Nonlinear Optimization / di Pillo G. ; Murli A.
Pages	s. 297-315
Number of pages	19 s.
Action	High Performance Algorithms and Software for Nonlinear Optimization
Event date	30.06.2001-08.07.2001
VEvent location	Erice
Country	IT - Italy
Event type	WRD
Language	eng - English
Country	NL - Netherlands
Keywords	semidefinite programming ; cone programming ; method of augmented Langrangians
Subject RIV	BA - General Mathematics
R&D Projects	GA201/00/0080 GA ČR - Czech Science Foundation (CSF)
CEZ	AV0Z1075907 - UTIA-B
Annotation	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.
Workplace	Institute of Information Theory and Automation
Contact	Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201.

Number of the records: 1