Abstract
Kojima, Megiddo, and Mizuno proved global convergence of a primal—dual algorithm that corresponds to methods used in practice. Here, the numerical efficiency of a predictor—corrector extension of that algorithm is tested. Numerical results are extremely positive, indicating that the safety of a globally convergent algorithm can be obtained at little computational cost. The algorithm is tested on infeasible problems with less success. Finally, the algorithm is applied to a warm started problem, with very encouraging preliminary results.
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Corresponding author. The research of this author is sponsored by the Air Force Office of Scientific Research, Air Force System Command under Grant AFOSR-92-J0046. The United States Government is authorized to reproduce and distribute reprints for governmental purposes notwithstanding any copyright notations thereon.
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Lustig, I.J., Marsten, R.E. & Shanno, D.F. Computational experience with a globally convergent primal—dual predictor—corrector algorithm for linear programming. Mathematical Programming 66, 123–135 (1994). https://doi.org/10.1007/BF01581140
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DOI: https://doi.org/10.1007/BF01581140