JOURNAL ARTICLE

Global convergence of conjugate gradient method in unconstrained optimization problems

Huda Y. NajmEman T. HamedHuda I. Ahmed

Year: 2019 Journal:   AIP conference proceedings Vol: 2091 Pages: 030029-030029   Publisher: American Institute of Physics

Abstract

In this study, we propose a new parameter in conjugate gradient method. It is shown that the new method fulfills the sufficient descent condition with the strong Wolfe condition when inexact line search has been used. The numerical results of this suggested method also shown that this method outperforms to other standard conjugate gradient method.

Keywords:
Conjugate gradient method Nonlinear conjugate gradient method Derivation of the conjugate gradient method Conjugate residual method Gradient descent Convergence (economics) Gradient method Line search Biconjugate gradient method Conjugate Computer science Applied mathematics Mathematical optimization Line (geometry) Mathematics Algorithm Mathematical analysis Artificial intelligence Artificial neural network Geometry

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5
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12
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0.75
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Citation History

Topics

Advanced Optimization Algorithms Research
Physical Sciences →  Mathematics →  Numerical Analysis
Sparse and Compressive Sensing Techniques
Physical Sciences →  Engineering →  Computational Mechanics
Iterative Methods for Nonlinear Equations
Physical Sciences →  Mathematics →  Numerical Analysis

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