General-purpose preconditioning for regularized interior point methods

Jacek Gondzio, Spyridon Pougkakiotis (Lead / Corresponding author), John W. Pearson

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)
32 Downloads (Pure)


In this paper we present general-purpose preconditioners for regularized augmented systems, and their corresponding normal equations, arising from optimization problems. We discuss positive definite preconditioners, suitable for CG and MINRES. We consider “sparsifications" which avoid situations in which eigenvalues of the preconditioned matrix may become complex. Special attention is given to systems arising from the application of regularized interior point methods to linear or nonlinear convex programming problems.

Original languageEnglish
Pages (from-to)727-757
Number of pages31
JournalComputational Optimization and Applications
Issue number3
Early online date14 Nov 2022
Publication statusPublished - Dec 2022


  • Convex optimization
  • Interior point methods
  • Krylov subspace methods
  • Preconditioning
  • Regularization
  • Saddle point systems

ASJC Scopus subject areas

  • Control and Optimization
  • Computational Mathematics
  • Applied Mathematics


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