A new efficient conjugate gradient method for unconstrained optimization

作者：Fatemi Masoud^*

来源：Journal of Computational and Applied Mathematics, 2016, 300: 207-216.

DOI：10.1016/j.cam.2015.12.035

• Conjugate gradient method
• Dai-Liao family
• Unconstrained optimization
• Line search

We propose a nonlinear conjugate gradient method for unconstrained optimization based on solving a new optimization problem. Our optimization problem combines the good features of the linear conjugate gradient method using some penalty parameters. We show that the new method is a subclass of Dai-Liao family, the fact that enables us to analyze the family, closely. As a consequence, we obtain an optimail bound for Dai-Liao parameter. The global convergence of the new method is investigated under mild assumptions. Numerical results show that the new method is efficient and robust, and outperforms CG-DESCENT.

• 出版日期2016-7