Convergence of a Proximal Point Algorithm for Solving Minimization Problems

被引：2

作者：

Hamdi, Abdelouahed ^{[1
]}

Noor, M. A. ^{[2
]}

Mukheimer, A. A. ^{[1
]}

机构：

[1] Prince Sultan Univ, Dept Math, Riyadh 11586, Saudi Arabia

[2] COMSATS Inst Informat Technol, Dept Math, Islamabad, Pakistan

来源：

JOURNAL OF APPLIED MATHEMATICS | 2012年

关键词：

VARIATIONAL-INEQUALITIES; BREGMAN FUNCTIONS;

D O I：

10.1155/2012/142862

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

We introduce and consider a proximal point algorithm for solving minimization problems using the technique of Guler. This proximal point algorithm is obtained by substituting the usual quadratic proximal term by a class of convex nonquadratic distance-like functions. It can be seen as an extragradient iterative scheme. We prove the convergence rate of this new proximal point method under mild assumptions. Furthermore, it is shown that this estimate rate is better than the available ones.

引用

页数：13

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