On the long-step path-following method for semidefinite programming

Jos F. Sturm, Shuzhong Zhang

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

It has been shown in various recent research reports that the analysis of short-step primal-dual path following algorithms for linear programming can be nicely generalized to semidefinite programming. However, the analysis of long-step pathfollowing algorithms for semidefinite programming appeared to be less straightforward. For such an algorithm, Monteiro (1997) obtained an O(n1.5 log(1/ε)) iteration bound for obtaining an ε-optimal solution, where n is the order of the semidefinite decision variable. In this paper, we propose to use a different search direction, viz. the so-called V-space direction. It is shown that this modification reduces the iteration complexity to O(n log(1/ε)). Independently, Monteiro and Y. Zhang obtained a similar result using Nesterov-Todd directions.

Original languageEnglish (US)
Pages (from-to)145-150
Number of pages6
JournalOperations Research Letters
Volume22
Issue number4-5
DOIs
StatePublished - Jan 1 1998

Keywords

  • Long-step path following
  • Semidefinite programming
  • Symmetric primal-dual transformation

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