A Homotopy Alternating Direction Method of Multipliers for Linearly Constrained Separable Convex Optimization

被引：2

作者：

Yang J. ^{[1
]}

Dai Y.-Q. ^{[2
]}

Peng Z. ^{[2
]}

Zhuang J.-P. ^{[2
]}

Zhu W.-X. ^{[2
]}

机构：

[1] Hunan Vocational Institute of Safety Technology, Changsha

[2] College of Mathematics and Computer Science, Fuzhou University, Fuzhou

来源：

Journal of the Operations Research Society of China | 2017年 / 5卷 / 02期

基金：

中国国家自然科学基金;

关键词：

Alternating direction method of multipliers; Homotopy method; Proximal point algorithm; Separable convex optimization;

D O I：

10.1007/s40305-017-0170-6

中图分类号：

学科分类号：

摘要：

Linearly constrained separable convex minimization problems have been raised widely in many real-world applications. In this paper, we propose a homotopy-based alternating direction method of multipliers for solving this kind of problems. The proposed method owns some advantages of the classical proximal alternating direction method of multipliers and homotopy method. Under some suitable conditions, we prove global convergence and the worst-case O(1k) convergence rate in a nonergodic sense. Preliminary numerical results indicate effectiveness and efficiency of the proposed method compared with some state-of-the-art methods. © 2017, Operations Research Society of China, Periodicals Agency of Shanghai University, Science Press, and Springer-Verlag Berlin Heidelberg.

引用

页码：271 / 290

页数：19

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