AN LQP-BASED DECOMPOSITION METHOD FOR SOLVING A CLASS OF VARIATIONAL INEQUALITIES

被引：30
|
作者：
Yuan, Xiaoming [1 ]
Li, Min [2 ]
机构：
[1] Hong Kong Baptist Univ, Dept Math, Hong Kong, Hong Kong, Peoples R China
[2] Southeast Univ, Sch Econ & Management, Nanjing 210096, Jiangsu, Peoples R China
来源：
SIAM JOURNAL ON OPTIMIZATION | 2011年 / 21卷 / 04期
基金：
中国国家自然科学基金;
关键词：
variational inequality; alternating direction method; logarithmic-quadratic proximal method; system of nonlinear equations; complementarity problem; ALTERNATING DIRECTIONS METHOD; ALGORITHM;
D O I：
10.1137/070703557
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
The alternating direction method (ADM) is an influential decomposition method for solving a class of variational inequalities with block-separable structures. In the literature, the subproblems of the ADM are usually regularized by quadratic proximal terms to ensure a more stable and attractive numerical performance. In this paper, we propose to apply the logarithmic-quadratic proximal (LQP) terms to regularize the ADM subproblems, and thus develop an LQP-based decomposition method for solving a class of variational inequalities. Global convergence of the new method is proved under standard assumptions.
引用
收藏
页码：1309 / 1318
页数：10
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