摘要
对一类由ＦｌｅｔｃｈｅｒＲｅｅｖｅｓ共轭梯度法控制的无约束极小化方法进行了研究，以一个简单的方式证明了一种非精确线性搜索条件能够保证该类方法的下降性和全局收敛性．该结果是对Ｇｉｌｂｅｒｔ和Ｎｏｃｅｄａｌ得到的结论的进一步扩展．
This paper investigates a class of methods for unconstrained minimization which is controlled by the FletcherReeves conjugate gradient method. In a simple way, we prove that a kind of inexact line search conditions can ensure the descent property and the convergence of this class of methods. Our result is a further extension of the conclusion that is given by Gilbert and Nocedal.
出处
《西安交通大学学报》
EI
CAS
CSCD
北大核心
1998年第6期100-102,共3页
Journal of Xi'an Jiaotong University
基金
国家自然科学基金
关键词
共轭梯度法
全局收敛性
无约束优化
conjugate gradient method global convergence unconstrained optimization largescale optimization line search
