Iterative methods for constrained convex minimization problem in Hilbert spaces

Fixexd point theory and applications

Ming Tian¹  Li-Hua Huang¹ 

[1] College of Science, Civil Aviation University of China, Tianjin, China

关键词: iterative algorithm;    constrained convex minimization;    nonexpansive mapping;    fixed point;    variational inequality;   

DOI  :  10.1186/1687-1812-2013-105

学科分类：数学（综合）

来源: SpringerOpen

【 摘 要 】

In this paper, based on Yamada’s hybrid steepest descent method, a general iterative method is proposed for solving constrained convex minimization problem. It is proved that the sequences generated by proposed implicit and explicit schemes converge strongly to a solution of the constrained convex minimization problem, which also solves a certain variational inequality. MSC:58E35, 47H09, 65J15.

【 授权许可】

CC BY