A general regularized gradient-projection method for solving equilibrium and constrained convex minimization problems

被引：0

作者：

Tian, Ming ^{[1
]}

Jiao, Si-Wen ^{[1
]}

机构：

[1] Civil Aviat Univ China, Coll Sci, Tianjin, Peoples R China

来源：

OPTIMIZATION | 2016年 / 65卷 / 11期

关键词：

Variational inequality; general iterative algorithms; equilibrium; constrained convex minimization; regularization methods; fixed point; 58E35; 47H09; 65J15; VISCOSITY APPROXIMATION METHODS; CQ ALGORITHM; FIXED-POINTS; FEASIBILITY; CONVERGENCE; SETS;

D O I：

10.1080/02331934.2016.1193738

中图分类号：

C93 [管理学]; O22 [运筹学];

学科分类号：

070105 ; 12 ; 1201 ; 1202 ; 120202 ;

摘要：

In this article, we provide a general iterative method for solving an equilibrium and a constrained convex minimization problem. By using the idea of regularized gradient-projection algorithm (RGPA), we find a common element, which is also a solution of a variational inequality problem. Then the strong convergence theorems are obtained under suitable conditions.

引用

页码：2007 / 2024

页数：18

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