Regularized gradient-projection methods for equilibrium and constrained convex minimization problems

被引：0

作者：

Tian, Ming ^{[1
]}

Huang, Li-Hua ^{[1
]}

机构：

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

来源：

JOURNAL OF INEQUALITIES AND APPLICATIONS | 2013年

关键词：

iterative method; constrained convex minimization; equilibrium; fixed point; variational inequality; VISCOSITY APPROXIMATION METHODS; NONEXPANSIVE-MAPPINGS; HILBERT-SPACES; FIXED-POINTS; VARIATIONAL-INEQUALITIES; ALGORITHMS; CONVERGENCE;

D O I：

10.1186/1029-242X-2013-243

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this article, based on Marino and Xu's method, an iterative method which combines the regularized gradient-projection algorithm (RGPA) and the averaged mappings approach is proposed for finding a common solution of equilibrium and constrained convex minimization problems. Under suitable conditions, it is proved that the sequences generated by implicit and explicit schemes converge strongly. The results of this paper extend and improve some existing results.

引用

页数：22

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