Global convergence of a memory gradient method without line search

被引：9
作者：
Yu Z. [1 ]
机构：
[1] College of Science, University of Shanghai for Science and Technology
来源：
Journal of Applied Mathematics and Computing | 2008年 / 26卷 / 1-2期
基金：
中国国家自然科学基金;
关键词：
Global convergence; Memory gradient; Unconstrained optimization; Without line search;
D O I：
10.1007/s12190-007-0021-4
中图分类号：
学科分类号：
摘要：
In this paper, we develop a memory gradient method for unconstrained optimization. The main characteristic of this method is that we obtain the next iteration without any line search. Under certain conditions, we obtain the strong global convergence of the proposed method. © 2007 KSCAM and Springer-Verlag.
引用
收藏
页码：545 / 553
页数：8
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