On the convergence analysis of inexact hybrid extragradient proximal point algorithms for maximal monotone operators

被引:13
|
作者
Ceng, Lu-Chuan [2 ]
Yao, Jen-Chih [1 ]
机构
[1] Natl Sun Yat Sen Univ, Dept Appl Math, Kaohsiung 804, Taiwan
[2] Shanghai Normal Univ, Dept Math, Shanghai 200234, Peoples R China
关键词
inexact hybrid extragradient proximal point algorithms; inexact iterative procedures; maximal monotone operator; weak convergence; strong convergence;
D O I
10.1016/j.cam.2007.02.010
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
In this paper we introduce general iterative methods for finding zeros of a maximal monotone operator in a Hilbert space which unify two previously studied iterative methods: relaxed proximal point algorithm [H.K. Xu, Iterative algorithms for nonlinear operators, J. London Math Soc. 66 (2002) 240-256] and inexact hybrid extragradient proximal point algorithm [R.S. Burachik, S. Scheimberg, B.F. Svaiter, Robustness of the hybrid extragradient proximal-point algorithm, J. Optim. Theory Appl. 111 (2001) 117-136]. The paper establishes both weak convergence and strong convergence of the methods under suitable assumptions on the algorithm parameters. (C) 2007 Elsevier B.V. All rights reserved.
引用
收藏
页码:326 / 338
页数:13
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