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Research Article · Open access · Published 5 July 2021

A New Spectral Conjugate Gradient Method for Nonlinear Unconstrained Optimization

Ibtisam A. Masmali1, Zabidin Salleh2 & Ahmad Alhawarat2

Journal of Computer Science, Volume 17, Issue 6, pp. 598–609 · doi.org/10.3844/jcssp.2021.598.609

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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.

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Masmali, I. A., Salleh, Z. & Alhawarat, A. (2021). A New Spectral Conjugate Gradient Method for Nonlinear Unconstrained Optimization. Journal of Computer Science, 17(6), 598–609. https://doi.org/10.3844/jcssp.2021.598.609

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A New Spectral Conjugate Gradient Method for Nonlinear Unconstrained OptimizationJournal of Computer Science · Volume 17, Issue 6 · pp. 598–609 · CC BY 4.0Download