GLOBAL CONVERGENCE PROPERTIES OF CONJUGATE GRADIENT METHODS FOR OPTIMIZATION

被引：727

作者：

Gilbert, Jean Charles ^{[1
]}

Nocedal, Jorge ^{[2
]}

机构：

[1] Inst Natl Rech Informat & Automat, F-78153 Le Chesnay, France

[2] Northwestern Univ, Dept Elect Engn & Comp Sci, Evanston, IL 60208 USA

来源：

SIAM JOURNAL ON OPTIMIZATION | 1992年 / 2卷 / 01期

基金：

美国能源部; 美国国家科学基金会;

关键词：

conjugate gradient method; global convergence; unconstrained optimization; large-scale optimization;

D O I：

10.1137/0802003

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

This paper explores the convergence of nonlinear conjugate gradient methods without restarts, and with practical line searches. The analysis covers two classes of methods that are globally convergent on smooth, nonconvex functions. Some properties of the Fletcher-Reeves method play an important role in the first family, whereas the second family shares an important property with the Polak-Ribiere method. Numerical experiments are presented.

引用

页码：21 / 42

页数：22

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