A family of hybrid conjugate gradient methods for unconstrained optimization

	A family of hybrid conjugate gradient methods for unconstrained optimization
	Dai, YH
	2003
发表期刊	MATHEMATICS OF COMPUTATION
ISSN	0025-5718
卷号	72 期号:243 页码:1317-1328
摘要	Conjugate gradient methods are an important class of methods for unconstrained optimization, especially for large-scale problems. Recently, they have been much studied. This paper proposes a three-parameter family of hybrid conjugate gradient methods. Two important features of the family are that (i) it can avoid the propensity of small steps, namely, if a small step is generated away from the solution point, the next search direction will be close to the negative gradient direction; and (ii) its descent property and global convergence are likely to be achieved provided that the line search satisfies the Wolfe conditions. Some numerical results with the family are also presented.
关键词	unconstrained optimization conjugate gradient method line search descent property global convergence
语种	英语
WOS研究方向	Mathematics
WOS类目	Mathematics, Applied
WOS记录号	WOS:000182344400012
出版者	AMER MATHEMATICAL SOC
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/19038
专题	计算数学与科学工程计算研究所
通讯作者	Dai, YH
作者单位	Chinese Acad Sci, Acad Math & Syst Sci, Inst Computat Math & Sci Engn Comp, State Key Lab Sci & Engn Comp, Beijing 100080, Peoples R China
推荐引用方式 GB/T 7714	Dai, YH. A family of hybrid conjugate gradient methods for unconstrained optimization[J]. MATHEMATICS OF COMPUTATION,2003,72(243):1317-1328.
APA	Dai, YH.(2003).A family of hybrid conjugate gradient methods for unconstrained optimization.MATHEMATICS OF COMPUTATION,72(243),1317-1328.
MLA	Dai, YH."A family of hybrid conjugate gradient methods for unconstrained optimization".MATHEMATICS OF COMPUTATION 72.243(2003):1317-1328.