An improved nonlinear conjugate gradient method with an optimal property. 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
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References in zbMATH (referenced in 4 articles )
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- Yao, Shengwei; Ning, Liangshuo: An adaptive three-term conjugate gradient method based on self-scaling memoryless BFGS matrix (2018)
- Dong, XiaoLiang; Liu, Hongwei; He, Yubo: A self-adjusting conjugate gradient method with sufficient descent condition and conjugacy condition (2015)
- Rivaie, Mohd; Mamat, Mustafa; Abashar, Abdelrhaman: A new class of nonlinear conjugate gradient coefficients with exact and inexact line searches (2015)
- Kou, Caixia: An improved nonlinear conjugate gradient method with an optimal property (2014)