Numerical Evaluation of SDPA (SemiDefinite Programming Algorithm)

Katsuki Fujisawa, Mituhiro Fukuda, Masakazu Kojima and Kazuhide Nakata

SDPA (SemiDefinite Programming Algorithm) is a C++ implementation of a Mehrotra-type primal-dual predictor-corrector interior-point method for solving the standard form semidefinite program and its dual. We report numerical results of large scale problems to evaluate its performance, and investigate how major time-consuming parts of SDPA vary with the problem size, the number of constraints and the sparsity of data matrices.

Research Report B-330, Department of Mathematical and Computing Sciences, Tokyo Institute of Technology, Oh-Okayama, Meguro-ku, Tokyo 152, September 1997.

Contact: kojima@is.titech.ac.jp


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