The convergence of a new method for large-scale box constrained variational inequality problem

被引：0
|
作者：
Zhu, Lin [1 ]
机构：
[1] Huaibei Normal Univ, Dept Math Sci, Huaibei, Peoples R China
来源：
FUZZY SYSTEM AND DATA MINING | 2016年 / 281卷
关键词：
Large-scale box constrained variational inequality; Inexact Newton method; Globally convergence; SMOOTHING NEWTON METHOD; GMRES;
D O I：
10.3233/978-1-61499-619-4-187
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we present an inexact Newton method for solving large-scale box constrained variational inequality problem. By using a smooth value function, the large-scale box constrained variational inequality problem is reformulated as a series of parameterized smooth equations. The corresponding linear equations is solved nearly in every iteration. Under the mild assumption, it is obtainable that the proposed algorithm is globally convergent.
引用
收藏
页码：187 / 194
页数：8
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