Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4641637 | Journal of Computational and Applied Mathematics | 2008 | 13 Pages |
Abstract
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.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Lu-Chuan Ceng, Jen-Chih Yao,