A Mixture Conjugate Gradient Method for Unconstrained Optimization

被引：1
|
作者：
Liu, Hailin [1 ]
机构：
[1] Guangdong Polytech Normal Univ, Sch Comp Sci, Guangzhou 510665, Guangdong, Peoples R China
来源：
2010 THIRD INTERNATIONAL SYMPOSIUM ON INTELLIGENT INFORMATION TECHNOLOGY AND SECURITY INFORMATICS (IITSI 2010) | 2010年
关键词：
conjugate gradient method; Wolve condition; sufficient descent; fixed point; unconstrained optimization;
D O I：
10.1109/IITSI.2010.57
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 conjugate gradient method for unconstrained optimization has been proposed, furthermore a mixture algorithm has been proposed, we have proved that the new method and the mixture method using inexact line search is sufficient descent and global convergent, and the numerical result shows that the new method is effective
引用
收藏
页码：26 / 29
页数：4
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