A modified nonlinear Polak-Ribiere-Polyak conjugate gradient method with sufficient descent property

被引：5

作者：

Dong, Xiaoliang ^{[1
,2
]}

机构：

[1] Xian Shiyou Univ, Coll Sci, Xian 710065, Peoples R China

[2] Nanjing Normal Univ, Sch Math Sci, Nanjing, Peoples R China

来源：

CALCOLO | 2020年 / 57卷 / 03期

基金：

中国国家自然科学基金;

关键词：

Polak-Ribiere-Polyak conjugate gradient method; Sufficient descent condition; Global convergence; Numerical comparison; GLOBAL CONVERGENCE; ALGORITHM;

D O I：

10.1007/s10092-020-00378-2

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this paper, a small and necessary revision on an assumption condition of Aminifard and Babaie-Kafaki (Calcolo, 2019. 10.1007/s10092-019-0312-9) is made. By a little modification, a new conjugate gradient method is proposed, in which the search directions satisfy the sufficient descent condition with the strong Wolfe line search. The main difference between two algorithms is that the proposed method is globally convergent without boundedness assumption on the steplength. Comparative numerical results demonstrating efficiency of the proposed method are reported.

引用

页数：14

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