Mehrotra-type predictor-corrector algorithm revisited
Optimization Methods & Software - Dedicated to Professor Michael J.D. Powell on the occasion of his 70th birthday
Further development of multiple centrality correctors for interior point methods
Computational Optimization and Applications
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We present convergence conditions for a generic primal-dual interior-point algorithm with multiple corrector directions. The corrector directions can be generated by any approach. The search direction is obtained by combining predictor and corrector directions through a small linear program. We also propose a new approach to generate corrector directions. This approach generates directions using information from an appropriately defined Krylov subspace. We propose efficient implementation strategies for our approach that follow the analysis of this paper. Numerical experiments illustrating the features of the proposed approach and its practical usefulness are reported.