ASYMPTOTIC CONVERGENCE ANALYSIS OF THE FORWARD-BACKWARD SPLITTING ALGORITHM

• 成果类型: Article
• 署名作者: ZHU, CY
• 刊物名称: MATHEMATICS OF OPERATIONS RESEARCH
• ISSN/ISSBN: 0364-765X
• DOI: 10.1287/moor.20.2.449
• 发表日期: 1995
• 页码: 449-464
• 关键词: proximal point algorithm; iterative methods; variational-inequalities; DECOMPOSITION

摘要

The asymptotic convergence of the forward-backward splitting algorithm for solving equations of type 0 is an element of T(z) is analyzed, where T is a multivalued maximal monotone operator in the n-dimensional Euclidean space, When the problem has a nonempty solution set, and T is split in the form T = J + h It with J being maximal monotone and h being co-coercive with modulus greater than 1/2, convergence rates are shown, under mild conditions, to be linear, superlinear or sublinear depending on how rapidly J(-1) and h(-1) grow in the neighborhoods of certain specific points. As a special case, when both J and h are polyhedral functions, we get R-linear convergence and 2-step e-linear convergence without any further assumptions on the strict monotonicity on T or on the uniqueness of the solution. As another special case when h = 0, the splitting algorithm reduces to the proximal point algorithm, and we get new results, which complement R. T. Rockafellar's and F. J. Luque's earlier results on the proximal point algorithm.