Convergence conditions and krylov subspace-based corrections for primal-dual interior-point method

Sanjay Mehrotra*, Zhifeng Li

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

12 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)635-653
Number of pages19
JournalSIAM Journal on Optimization
Issue number3
StatePublished - Aug 26 2005


  • Convergence
  • Inexact search direction
  • Krylov subspace
  • Linear program
  • Primal-dual interior-point method

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science


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