Warm-start strategies in interior-point methods for linear programming

E. Alper Yildirim*, Stephen J. Wright

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


We study the situation in which, having solved a linear program with an interiorpoint method, we are presented with a new problem instance whose data is slightly perturbed from the original. We describe strategies for recovering a "warm-start" point for the perturbed problem instance from the iterates of the original problem instance. We obtain worst-case estimates of the number of iterations required to converge to a solution of the perturbed instance from the warm-start points, showing that these estimates depend on the size of the perturbation and on the conditioning and other properties of the problem instances.

Original languageEnglish
Pages (from-to)782-810
Number of pages29
JournalSiam journal on optimization
Issue number3
Publication statusPublished - 1 Jan 2002


  • Interior-point methods
  • Linear programming
  • Reoptimizatiou
  • Warm-start


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