A new nonlinear conjugate gradient coefficient under strong Wolfe-Powell line search

A nonlinear conjugate gradient method (CG) plays an important role in solving a large-scale unconstrained optimization problem. This method is widely used due to its simplicity. The method is known to possess sufficient descend condition and global convergence properties. In this paper, a new nonlin...

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Bibliographic Details
Main Authors: Mohamed, Nur Syarafina, Mamat, Mustafa, Rivaie, Mohd
Format: Conference Proceeding
Language:English
Subjects:
Central processing units
Conjugate gradient method
Conjugates
Convergence
CPUs
Microprocessors
Online Access:Get full text
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Summary:A nonlinear conjugate gradient method (CG) plays an important role in solving a large-scale unconstrained optimization problem. This method is widely used due to its simplicity. The method is known to possess sufficient descend condition and global convergence properties. In this paper, a new nonlinear of CG coefficient β k is presented by employing the Strong Wolfe-Powell inexact line search. The new β k performance is tested based on number of iterations and central processing unit (CPU) time by using MATLAB software with Intel Core i7-3470 CPU processor. Numerical experimental results show that the new β k converge rapidly compared to other classical CG method.
ISSN:0094-243X
1551-7616
DOI:10.1063/1.4995887