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Journal of Applied Mathematics
Volume 2003 (2003), Issue 10, Pages 517-534

Convergence of a short-step primal-dual algorithm based on the Gauss-Newton direction

1Department of Mathematics and Statistics, Oakland University, Rochester 48309, MI, USA
2Department of Combinatorics and Optimization, University of Waterloo, Waterloo, Ontario, Canada N2L 3G1

Received 23 January 2003; Revised 9 April 2003

Copyright © 2003 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


We prove the theoretical convergence of a short-step, approximate path-following, interior-point primal-dual algorithm for semidefinite programs based on the Gauss-Newton direction obtained from minimizing the norm of the perturbed optimality conditions. This is the first proof of convergence for the Gauss-Newton direction in this context. It assumes strict complementarity and uniqueness of the optimal solution as well as an estimate of the smallest singular value of the Jacobian.