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.
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页码：187 / 194
页数：8
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