Improved Complexity Analysis of Full Nesterov–Todd Step Feasible Interior-Point Method for Symmetric Optimization

G. Q. Wang, L. C. Kong, J. Y. Tao, G. Lesaja

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

In this paper, an improved complexity analysis of full Nesterov–Todd step feasible interior-point method for symmetric optimization is considered. Specifically, we establish a sharper quadratic convergence result using several new results from Euclidean Jordan algebras, which leads to a wider quadratic convergence neighbourhood of the central path for the iterates in the algorithm. Furthermore, we derive the currently best known iteration bound for full Nesterov–Todd step feasible interior-point method.

Original languageEnglish
Pages (from-to)588-604
Number of pages17
JournalJournal of Optimization Theory and Applications
Volume166
Issue number2
DOIs
StatePublished - Aug 25 2015

Scopus Subject Areas

  • Control and Optimization
  • Management Science and Operations Research
  • Applied Mathematics

Keywords

  • Euclidean Jordan algebras
  • Full Nesterov–Todd step
  • Interior-point methods
  • Linear optimization over symmetric cones
  • Polynomial complexity

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