Linear Regularity and Linear Convergence of Projection-Based Methods for Solving Convex Feasibility Problems

被引:126
|
作者
Zhao, Xiaopeng [1 ]
Ng, Kung Fu [2 ]
Li, Chong [3 ]
Yao, Jen-Chih [4 ,5 ]
机构
[1] Tianjin Polytech Univ, Dept Math, Tianjin 300387, Peoples R China
[2] Chinese Univ Hong Kong, Dept Math, Hong Kong, Hong Kong, Peoples R China
[3] Zhejiang Univ, Sch Math Sci, Hangzhou 310027, Zhejiang, Peoples R China
[4] China Med Univ, Ctr Gen Educ, Taichung 40402, Taiwan
[5] Kaohsiung Med Univ, Res Ctr Nonlinear Anal & Optimizat, Kaohsiung 807, Taiwan
来源
APPLIED MATHEMATICS AND OPTIMIZATION | 2018年 / 78卷 / 03期
基金
中国国家自然科学基金;
关键词
Convex feasibility problem; Linear regularity; Projection algorithm; STRONG CHIP; HILBERT-SPACE; INFINITE SYSTEM; ERROR-BOUNDS; SETS; OPTIMIZATION; ALGORITHMS;
D O I
10.1007/s00245-017-9417-1
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
For a finite/infinite family of closed convex sets with nonempty intersection in Hilbert space, we consider the (bounded) linear regularity property and the linear convergence property of the projection-based methods for solving the convex feasibility problem. Several sufficient conditions are provided to ensure the bounded linear regularity in terms of the interior-point conditions and some finite codimension assumptions. A unified projection method, called Algorithm B-EMOPP, for solving the convex feasibility problem is proposed, and by using the bounded linear regularity, the linear convergence results for this method are established under a new control strategy introduced here.
引用
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页码:613 / 641
页数:29
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