摘要
基于Dai-Yuan共轭梯度法,本文给出了求解无约束优化的一个非线性共轭梯度法.对任意的线性搜索,该方法满足充分下降条件gTkdk≤-(1-1/4μ)‖gk‖2,μ>1/4;而且,对一般的非线性函数,不需限制的下限值,用Wolf线搜索具有全局收敛性.
In this paper,based on the Dai-Yuan conjugate gradient method,a new nonlinear conjugate gradient method is proposed for the unconstrained optimization.For any line search,our scheme satisfies the sufficient descent condition. gTkdk≤-（1-1/4μ）‖gk‖2,μ1/4.Moreover,a global convergence resulted from general nonlinear function is established when the standard Wolf line search is used under some suitable conditions without restricting the lower value of βNk.
出处
《邵阳学院学报（自然科学版）》
2010年第4期9-11,共3页
Journal of Shaoyang University：Natural Science Edition
基金
湖南省教育厅课题(09C565)
关键词
无约束优化
共轭梯度法
Wolf条件
全局收敛性
unconstrained optimization
conjugate gradient method
Wolf condition
global convergence
