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[PENNON - A Generalized Augmented Lagrangian Methodfor Semidefinite Programming

Michal Kocvara (kocvara***at***am.uni-erlangen.de)
Michael Stingl (stingl***at***am.uni-erlangen.de)

Abstract: 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 and comparison with other SDP codes are presented.

Keywords: semidefinite programming; cone programming; method of augmented Lagrangians

Category 1: Linear, Cone and Semidefinite Programming (Semi-definite Programming )

Category 2: Linear, Cone and Semidefinite Programming (Second-Order Cone Programming )

Category 3: Applications -- Science and Engineering (Mechanical Engineering )

Citation: Research Report 286, Institute of Applied Mathematics, University of Erlangen, 2001.

Download: [Compressed Postscript][PDF]

Entry Submitted: 12/18/2001
Entry Accepted: 12/18/2001
Entry Last Modified: 12/18/2001

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