Global convergence of a modified spectral FR conjugate gradient method

被引：30

作者：

Du, Shou-qiang ^{[1
,2
]}

Chen, Yuan-yuan ^{[2
]}

机构：

[1] Shanghai Univ Sci & Technol, Sch Management, Shanghai 200093, Peoples R China

[2] Qingdao Univ, Coll Math, Qingdao 266071, Peoples R China

来源：

APPLIED MATHEMATICS AND COMPUTATION | 2008年 / 202卷 / 02期

基金：

中国国家自然科学基金;

关键词：

unconstrained optimization; conjugate gradient method; line search; global convergence;

D O I：

10.1016/j.amc.2008.03.020

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

This paper deals with a new nonlinear modified spectral FR conjugate gradient method for solving large scale unstrained optimization problems. The direction generated by the method is a descent direction for the objective function. Under mild conditions, we prove that the modified spectral FR conjugate gradient method with Wolfe type line search is globally convergent. Preliminary numerical results show the proposed method is very promising. (C) 2008 Elsevier Inc. All rights reserved.

引用

页码：766 / 770

页数：5

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