Iterative algorithms based on the viscosity approximation method for equilibrium and constrained convex minimization problem

被引：11

作者：

Tian, Ming ^{[1
]}

Liu, Lei ^{[1
]}

机构：

[1] Civil Aviat Univ China, Coll Sci, Tianjin 300300, Peoples R China

来源：

FIXED POINT THEORY AND APPLICATIONS | 2012年

关键词：

iterative algorithm; equilibrium problem; constrained convex minimization; variational inequality; FIXED-POINT PROBLEMS; HILBERT-SPACES; NONEXPANSIVE-MAPPINGS; STRONG-CONVERGENCE; OPTIMIZATION;

D O I：

10.1186/1687-1812-2012-201

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

The gradient-projection algorithm (GPA) plays an important role in solving constrained convex minimization problems. Based on the viscosity approximation method, we combine the GPA and averaged mapping approach to propose implicit and explicit composite iterative algorithms for finding a common solution of an equilibrium and a constrained convex minimization problem for the first time in this paper. Under suitable conditions, strong convergence theorems are obtained. MSC: 46N10, 47J20, 74G60.

引用

页码：1 / 17

页数：17

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