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Journal of Engineering and Applied Sciences

A New Scaled Steepest Descent Method for Unconstrained Optimization with Global Convergence Properties
Rashidah Johari, Mohd Rivaie and Mustafa Mamat

Abstract: The steepest descent method is the simplest gradient method for solving unconstrained optimization problems. In this study, a new scaled search direction of steepest descent method is proposed. The proposed method is motivated by Andrei’s approach of scaled conjugate gradient method. The numerical results show that the proposed method outperforms than the other classical steepest descent method.

How to cite this article
Rashidah Johari, Mohd Rivaie and Mustafa Mamat, 2018. A New Scaled Steepest Descent Method for Unconstrained Optimization with Global Convergence Properties. Journal of Engineering and Applied Sciences, 13: 5442-5445.

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