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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Main Authors: | , , |
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Format: | Conference or Workshop Item |
Language: | English |
Published: |
2017
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Subjects: | |
Online Access: | http://eprints.unisza.edu.my/1518/1/FH03-FIK-17-09952.jpg http://eprints.unisza.edu.my/1518/ |
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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 βk is presented by employing the Strong Wolfe-Powell inexact line search. The new βk 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 βk converge rapidly compared to other classical CG method. |
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