A New Spectral Conjugate Gradient Method for Nonlinear Unconstrained Optimization
- 1 Jazan University, Saudi Arabia
- 2 University Malaysia Terengganu, Malaysia
Abstract
Theconjugate gradient method is widely used to solve large scale unconstrainedoptimization problems. However, the rate of convergence conjugate gradient method is linearunless it restarted. In this study, we present a new spectral conjugategradient modification formula with restart property obtains the globalconvergence and descent properties.In addition, we proposed a new restart condition for Fletcher-Reeves conjugate gradient formula. The numerical resultsdemonstrated that the modified Fletcher-Reeves parameter and the new CG formulawith their restart conditions are more efficient and robustness than otherconventional methods.
DOI: https://doi.org/10.3844/jcssp.2021.598.609
Copyright: © 2021 Ibtisam A. Masmali, Zabidin Salleh and Ahmad Alhawarat. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Keywords
- Conjugate Gradient
- Global Convergence
- Descent Condition