Regularized gradient-projection methods for the constrained convex minimization problem and the zero points of maximal monotone operator

Fixexd point theory and applications

Ming Tian¹  Si-Wen Jiao² 

[1] College of Science, Civil Aviation University of China, Tianjin, China;Tianjin Key Laboratory for Advanced Signal Processing, Civil Aviation University of China, Tianjin, China

关键词: iterative method;    fixed point;    constrained convex minimization;    maximal monotone operator;    resolvent;    equilibrium problem;    variational inequality;    58E35;    47H09;    65J15;   

DOI  :  10.1186/s13663-015-0258-9

学科分类：数学（综合）

来源: SpringerOpen

【 摘 要 】

In this paper, based on the viscosity approximation method and the regularized gradient-projection algorithm, we find a common element of the solution set of a constrained convex minimization problem and the set of zero points of the maximal monotone operator problem. In particular, the set of zero points of the maximal monotone operator problem can be transformed into the equilibrium problem. Under suitable conditions, new strong convergence theorems are obtained, which are useful in nonlinear analysis and optimization. As an application, we apply our algorithm to solving the split feasibility problem and the constrained convex minimization problem in Hilbert spaces.

【 授权许可】

CC BY