An Interior Point Method for Solving Semidefinite Programs Using Cutting Planes and Weighted Analytic Centers

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...

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Main Authors: John Machacek, Shafiu Jibrin
Format: Article
Language:English
Published: Wiley 2012-01-01
Series:Journal of Applied Mathematics
Online Access:http://dx.doi.org/10.1155/2012/946893
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author John Machacek
Shafiu Jibrin
author_facet John Machacek
Shafiu Jibrin
author_sort John Machacek
collection DOAJ
description 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.
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spelling doaj-art-e097bd13246f4e21aaba210170d8b6242025-02-03T05:58:54ZengWileyJournal of Applied Mathematics1110-757X1687-00422012-01-01201210.1155/2012/946893946893An Interior Point Method for Solving Semidefinite Programs Using Cutting Planes and Weighted Analytic CentersJohn Machacek0Shafiu Jibrin1Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN 55455, USADepartment of Mathematics and Statistics, Northern Arizona University, Flagstaff, Arizona 86011-5717, USAWe 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.http://dx.doi.org/10.1155/2012/946893
spellingShingle John Machacek
Shafiu Jibrin
An Interior Point Method for Solving Semidefinite Programs Using Cutting Planes and Weighted Analytic Centers
Journal of Applied Mathematics
title An Interior Point Method for Solving Semidefinite Programs Using Cutting Planes and Weighted Analytic Centers
title_full An Interior Point Method for Solving Semidefinite Programs Using Cutting Planes and Weighted Analytic Centers
title_fullStr An Interior Point Method for Solving Semidefinite Programs Using Cutting Planes and Weighted Analytic Centers
title_full_unstemmed An Interior Point Method for Solving Semidefinite Programs Using Cutting Planes and Weighted Analytic Centers
title_short An Interior Point Method for Solving Semidefinite Programs Using Cutting Planes and Weighted Analytic Centers
title_sort interior point method for solving semidefinite programs using cutting planes and weighted analytic centers
url http://dx.doi.org/10.1155/2012/946893
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