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An improved Wei–Yao–Liu nonlinear conjugate gradient method for optimization computation

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成果类型:
期刊论文
作者:
Zhang, Li*
通讯作者:
Zhang, Li
作者机构:
[Zhang, Li; Zhang, L] Changsha Univ Sci & Technol, Coll Math & Computat Sci, Changsha 410076, Hunan, Peoples R China.
通讯机构:
[Zhang, Li] C
Changsha Univ Sci & Technol, Coll Math & Computat Sci, Changsha 410076, Hunan, Peoples R China.
语种:
英文
关键词:
Conjugate gradient method;Descent direction;Global convergence
期刊:
Applied Mathematics and Computation
ISSN:
0096-3003
年:
2009
卷:
215
期:
6
页码:
2269-2274
基金类别:
This work was supported by the NSF foundation ( 10701018 ) of China and a project of Scientific Research Fund of Hunan Provincial Education Department.
机构署名:
本校为第一且通讯机构
院系归属:
数学与统计学院
摘要:
In this paper, we take a little modification to the Wei-Yao-Liu nonlinear conjugate gradient method proposed by Wei et al. [Z. Wei, S. Yao, L. Liu, The convergence properties of some new conjugate gradient methods, Appl. Math. Comput. 183 (2006) 1341-1350] such that the modified method possesses better convergence properties. In fact, we prove that the modified method satisfies sufficient descent condition with greater parameter σ ∈ fenced(0, frac(1, 2)) in the strong Wolfe line search and converges globally for nonconvex minimization. We als...

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