An interior point method for solving semidefinite programs using cutting planes and weighted analytic centers

John MacHacek, Shafiu Jibrin

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

We investigate solving semidefinite programs (SDPs) with an interior point method called SDP-CUT, which utilizes weighted analytic centers and cutting plane constraints. SDP-CUT iteratively refines the feasible region to achieve the optimal solution. The algorithm uses Newton's method to compute the weighted analytic center. We investigate different stepsize determining techniques. We found that using Newton's method with exact line search is generally the best implementation of the algorithm. We have also compared our algorithm to the SDPT3 method and found that SDP-CUT initially gets into the neighborhood of the optimal solution in less iterations on all our test problems. SDP-CUT also took less iterations to reach optimality on many of the problems. However, SDPT3 required less iterations on most of the test problems and less time on all the problems. Some theoretical properties of the convergence of SDP-CUT are also discussed.

Original languageEnglish (US)
Article number946893
JournalJournal of Applied Mathematics
Volume2012
DOIs
StatePublished - 2012

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Analytic Center
Semidefinite Program
Cutting Planes
Interior Point Method
Newton-Raphson method
Iteration
Newton Methods
Test Problems
Optimal Solution
Feasible region
Line Search
Optimality

ASJC Scopus subject areas

  • Applied Mathematics

Cite this

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