A modified alternating direction method for convex quadratically constrained quadratic semidefinite programs |
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Authors: | Jie Sun Su Zhang |
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Institution: | 1. Department of Decision Sciences and Risk Management Institute, National University of Singapore, Singapore 119245, Singapore;2. Department of Decision Sciences, National University of Singapore and Institute of Modern Management, Business School, Nankai University, PR China |
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Abstract: | We propose a modified alternating direction method for solving convex quadratically constrained quadratic semidefinite optimization problems. The method is a first-order method, therefore requires much less computational effort per iteration than the second-order approaches such as the interior point methods or the smoothing Newton methods. In fact, only a single inexact metric projection onto the positive semidefinite cone is required at each iteration. We prove global convergence and provide numerical evidence to show the effectiveness of this method. |
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Keywords: | Alternating direction method Conic programming Quadratic semidefinite optimization |
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