Superlinear convergence of a predictor-corrector
method for semidefinite programming without shrinking
central path neighborhood
Florian A. Potra and Rongqin Sheng
An infeasible start predictor-corrector algorithm for
semidefinite programming is proposed. It is a direct extension of the
Mizuno-Todd-Ye predictor-corrector algorithm for linear programming.
The algorithm uses the
in the predictor step and the Alizadeh-Haeberly-Overton direction
in the corrector step. It has polynomial complexity
for general problems and is
superlinearly convergent with $Q$-order at least 1.5 under strict
complementarity and nondegeneracy conditions.
Reports on Computational Mathematics, No. 91,
Department of Mathematics, The University of Iowa,