A trust region method for solving semidefinite programs

Aiqun Huang () and Chengxian Xu ()

Computational Optimization and Applications, 2013, vol. 55, issue 1, 49-71

Abstract: When using interior point methods for solving semidefinite programs (SDP), one needs to solve a system of linear equations at each iteration. For problems of large size, solving the system of linear equations can be very expensive. In this paper, we propose a trust region algorithm for solving SDP problems. At each iteration we perform a number of conjugate gradient iterations, but do not need to solve a system of linear equations. Under mild assumptions, the convergence of this algorithm is established. Numerical examples are given to illustrate the convergence results obtained. Copyright Springer Science+Business Media New York 2013

Keywords: Semidefinite programming; Fréchet derivative; Global convergence; Trust region method (search for similar items in EconPapers)
Date: 2013
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DOI: 10.1007/s10589-012-9514-7

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