A New Family Sufficient Descent Conjugate Gradient Methods for Unconstrained Optimization

被引：0

作者：

Sun, Zhongbo ^{[1
]}

Zhu, Tianxiao ^{[2
]}

Weng, Shiyou ^{[3
]}

Gao, Haiyin ^{[2
]}

机构：

[1] Northeast Normal Univ, Coll Humanities & Sci, Changchun 130117, Peoples R China

[2] Changchun Univ, Coll Sci, Changchun 130022, Peoples R China

[3] Suzhou Vocat Univ, Dept Basic Course, Suzhou, Peoples R China

来源：

PROCEEDINGS OF THE 31ST CHINESE CONTROL CONFERENCE | 2012年

关键词：

conjugate gradient method; sufficient descent direction; unconstrained minimizing optimization problems; GLOBAL CONVERGENCE; MINIMIZATION;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, a new family modified descent conjugate gradient methods are proposed for solving unconstrained optimization problems. We develop a new sufficient descent direction at every iteration. Under some suitable conditions, theoretical analysis shows that the algorithm is global convergence. Numerical results show that this method is effective in unconstrained minimizing optimization problems.

引用

页码：2532 / 2536

页数：5

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