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2014 A Line-Search-Based Partial Proximal Alternating Directions Method for Separable Convex Optimization
Yu-hua Zeng, Yu-fei Yang, Zheng Peng
J. Appl. Math. 2014: 1-8 (2014). DOI: 10.1155/2014/540450

Abstract

We propose an appealing line-search-based partial proximal alternating directions (LSPPAD) method for solving a class of separable convex optimization problems. These problems under consideration are common in practice. The proposed method solves two subproblems at each iteration: one is solved by a proximal point method, while the proximal term is absent from the other. Both subproblems admit inexact solutions. A line search technique is used to guarantee the convergence. The convergence of the LSPPAD method is established under some suitable conditions. The advantage of the proposed method is that it provides the tractability of the subproblem in which the proximal term is absent. Numerical tests show that the LSPPAD method has better performance compared with the existing alternating projection based prediction-correction (APBPC) method if both are employed to solve the described problem.

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Yu-hua Zeng. Yu-fei Yang. Zheng Peng. "A Line-Search-Based Partial Proximal Alternating Directions Method for Separable Convex Optimization." J. Appl. Math. 2014 1 - 8, 2014. https://doi.org/10.1155/2014/540450

Information

Published: 2014
First available in Project Euclid: 2 March 2015

zbMATH: 07131678
MathSciNet: MR3208629
Digital Object Identifier: 10.1155/2014/540450

Rights: Copyright © 2014 Hindawi

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