New conjugacy conditions and related nonlinear conjugate gradient methods

被引:378
作者
Dai, YH
Liao, LZ
机构
[1] Chinese Acad Sci, Acad Math & Syst Sci, Inst Computat Math & Sci Engn Comp, State Key Lab Sci & Engn Comp, Beijing 100080, Peoples R China
[2] Hong Kong Baptist Univ, Dept Math, Kowloon, Hong Kong, Peoples R China
关键词
unconstrained optimization; conjugate gradient; line search; global convergence;
D O I
10.1007/s002450010019
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Conjugate gradient methods are a class of important methods for unconstrained optimization, especially when the dimension is large. This paper proposes a new conjugacy condition, which considers an inexact line search scheme but reduces to the old one if the line search is exact. Based on the new conjugacy condition, two nonlinear conjugate gradient methods are constructed. Convergence analysis for the two methods is provided. Our numerical results show that one of the methods is very efficient for the given test problems.
引用
收藏
页码:87 / 101
页数:15
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