Strong convergence for an iterative method for the triple-hierarchical constrained optimization problem

被引：36

作者：

Iiduka, Hideaki ^{[1
]}

机构：

[1] Kyushu Inst Technol, Network Design Res Ctr, Chiyoda Ku, Tokyo 1000011, Japan

来源：

NONLINEAR ANALYSIS-THEORY METHODS & APPLICATIONS | 2009年 / 71卷 / 12期

关键词：

Hierarchical constrained optimization problem; Variational inequality problem; Monotone operator; Nonexpansive mapping; Fixed point; Strong convergence; COMMON FIXED-POINT; VARIATIONAL-INEQUALITIES; CONSTRUCTION; ALGORITHMS; MAPPINGS;

D O I：

10.1016/j.na.2009.01.133

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

The variational inequality problem for a monotone operator over the fixed point set of a nonexpansive mapping is connected with many signal processing problems, and such problems have hierarchical structure, for example, the convex optimization problem over the solution set of the variational inequality problem over the fixed point set has triple-hierarchical structure. In this paper, we present an iterative algorithm for this problem. The strong convergence for the proposed algorithm to the solution is guaranteed under some assumptions. (C) 2009 Elsevier Ltd. All rights reserved.

引用

页码：E1292 / E1297

页数：6

共 39 条

[11] A block-iterative surrogate constraint splitting method for quadratic signal recovery [J].