Interior point method on semi-definite linear complementarity problems using the Nesterov-Todd (NT) search direction: polynomial complexity and local convergence

Research output: Contribution to journalArticlepeer-review

62 Downloads (Pure)

Abstract

We consider in this paper an infeasible predictor-corrector primal-dual path following interior point algorithm using the Nesterov-Todd (NT) search direction to solve semi-definite linear complementarity problems. Global convergence and polynomial iteration complexity of the algorithm are established. Two sufficient conditions are also given for superlinear convergence of iterates generated by the algorithm. Preliminary numerical results are finally provided when the algorithm is used to solve semi-definite linear complementarity problems.
Original languageEnglish
Article number0
Pages (from-to)583-621
Number of pages39
JournalComputational Optimization and Applications
Volume74
Issue number2
Early online date22 May 2019
DOIs
Publication statusPublished - 1 Nov 2019

Keywords

  • Nesterov-Todd (NT) Direction
  • Predictor-Corrector Primal-Dual Path Following Interior Point Algorithm
  • Semi-definite Linear Complementarity Problem
  • Polynomial Complexity
  • Local Convergence

Fingerprint

Dive into the research topics of 'Interior point method on semi-definite linear complementarity problems using the Nesterov-Todd (NT) search direction: polynomial complexity and local convergence'. Together they form a unique fingerprint.

Cite this