A conjugate gradient method with inexact line search for unconstrained optimization
In this paper, an efficient nonlinear modified PRP conjugate gradient method is presented for solving large-scale unconstrained optimization problems. The sufficient descent property is satisfied under strong Wolfe-Powell (SWP) line search by restricting the parameter 1/ 4 . The global convergenc...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English English |
| Published: |
HIKARI Ltd.
2015
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| Subjects: | |
| Online Access: | http://eprints.unisza.edu.my/6234/1/FH02-FIK-15-03335.pdf http://eprints.unisza.edu.my/6234/2/FH02-FIK-15-03429.jpg http://eprints.unisza.edu.my/6234/ |
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| Institution: | Universiti Sultan Zainal Abidin |
| Language: | English English |
| Summary: | In this paper, an efficient nonlinear modified PRP conjugate gradient method is presented for solving large-scale unconstrained optimization problems. The sufficient descent property is satisfied under strong Wolfe-Powell (SWP) line search by restricting the parameter 1/ 4 . The global convergence result is established under the (SWP) line search conditions. Numerical results, for a set consisting of 133 unconstrained optimization test problems, show that this method is better than the PRP method and the FR method. |
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