A new class of Conjugate Gradient Methods with extended Nonmonotone Line Search

被引：0
|
作者：
Liu, Hailin [1 ]
Li, Xiaoyong [2 ]
机构：
[1] Guangdong Polytech Normal Univ, Sch Comp Sci, Guangzhou 510665, Guangdong, Peoples R China
[2] Univ Toulouse 3, Lab Collis Agrgats Ractivit, F-31062 Toulouse 09, France
来源：
APPLIED MATHEMATICS & INFORMATION SCIENCES | 2012年 / 6卷
关键词：
Conjugate gradient; Sufficient descent; Hybrid method; Unconstrained optimization; GLOBAL CONVERGENCE; MINIMIZATION; PROPERTY; DESCENT;
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, we propose a new nonlinear conjugate gradient method for large-scale unconstrain optimization which possesses the following properties:(i)the sufficient descent condition -g(k)(T)d(k) >= 7/8 parallel to gk parallel to(2) holds without any line searchcs;(ii)With exact line search, this method reduces to a nonlinear version of the Liu-Storey conjugate gradient scheme.(iii)Under some assumption, global convergence of this method is proved with a new nonmonotone line search.Preliminary numerical results show that this method is very efficient.
引用
收藏
页码：147 / 154
页数：8
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