[PENNON – A Generalized Augmented Lagrangian Methodfor Semidefinite Programming

  • Michal Kočvara
  • Michael Stingl
    • Categories Mechanical Engineering, Second-Order Cone Programming, Semi-definite Programming Short URL: https://optimization-online.org/?p=9187

    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.

    Citation

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

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