摘要
Conjugate gradient methods have played a special role in solving large scale nonlinear problems. Recently, the author and Dai proposed an efficient nonlinear conjugate gradient method called CGOPT, through seeking the conjugate gradient direction closest to the direction of the scaled memoryless BFGS method. In this paper, we make use of two types of modified secant equations to improve CGOPT method. Under some assumptions, the improved methods are showed to be globally convergent. Numerical results are also reported.
Conjugate gradient methods have played a special role in solving large scale nonlinear problems.Recently,the author and Dai proposed an efcient nonlinear conjugate gradient method called CGOPT,through seeking the conjugate gradient direction closest to the direction of the scaled memoryless BFGS method.In this paper,we make use of two types of modified secant equations to improve CGOPT method.Under some assumptions,the improved methods are showed to be globally convergent.Numerical results are also reported.
基金
supported by National Natural Science Foundation of China(Grant Nos.10831006 and 10971017)
