GLOBAL CONVERGENCE OF MODIFIED HS CONJUGATE GRADIENT METHOD

被引：0

作者：

Sun Qingying ^{[1
]}

Liu Qiu ^{[1
]}

机构：

[1] China Univ Petr, Sch Math & Computat Sci, Dongying 257061, Peoples R China

来源：

JOURNAL OF APPLIED MATHEMATICS AND COMPUTING | 2006年 / 22卷 / 03期

基金：

中国国家自然科学基金;

关键词：

Non-linear programming; memory gradient method; Curry-Altman's step size rule; Armijo step size rule; convergence; numerical experiment;

D O I：

暂无

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this paper, HS conjugate gradient method for minimizing a continuously differentiable function f on R-n is modified to have global convergence property. Firstly, it is shown that, using reverse modulus of continuity function and forcing function, the new method for solving unconstrained optimization can work for a continuously differentiable function with Curry-Altman's step size rule and a bounded level set. Secondly, by using comparing technique, some general convergence properties of the new method with Armijo step size rule are established. Numerical results show that the new algorithms are efficient.

引用

页码：289 / 297

页数：9