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所属单位：

中南大学

发表刊物：

Journal of Pacific Optimization

刊物所在地：

Japan

关键字：

unconstrained optimization; three-term conjugate gradient method; global convergence; Armijo-type

摘要：

In this paper, a new Dai-Liao type of three-term conjugate gradient algorithm is developed for solving nonconvex unconstrained optimization problems. The search direction consists of three terms, which aim to gather more useful information of the current iterate point such that the direction has better convergence performance for the algorithm. Different from the existing methods, global convergence is established without assumption of uniform convexity under a modified Armijo-type line search. Numerical experiments are employed to show efficiency of the algorithm in solving large-sca

合写作者：

Jing Lv

第一作者：

Songhai Deng

论文类型：

基础研究

通讯作者：

Zhong Wan

文献类型：

J

ISSN号：

1349-8169

是否译文：

否

发表时间：

2018-11-09