A new efficient conjugate gradient method for unconstrained optimization

JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS

卷:300

Article

Fatemi, Masoud^1,2 

[1] KN Toosi Univ Technol, Dept Math, Tehran, Iran

[2] KN Toosi Univ Technol, Sci Computat Optimizat & Syst Engn SCOPE, Tehran, Iran

关键词: Conjugate gradient method;    Dai-Liao family;    Unconstrained optimization;    Line search;   

DOI  :  10.1016/j.cam.2015.12.035

来源: Elsevier

【 摘 要 】

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. (C) 2016 Elsevier B.V. All rights reserved.

【 授权许可】

Free