New modification of the hestenes-stiefel with strong wolfe line search
. The method of the nonlinear conjugate gradient is widely used in solving large-scale unconstrained optimization since been proven in solving optimization problems without using large memory storage. In this paper, we proposed a new modification of the Hestenes-Stiefel conjugate gradient parameter...
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my.uthm.eprints.26432021-10-25T08:57:16Z http://eprints.uthm.edu.my/2643/ New modification of the hestenes-stiefel with strong wolfe line search Japri, Nur Athira Basri, Srimazzura Mamat, Mustafa QC Physics . The method of the nonlinear conjugate gradient is widely used in solving large-scale unconstrained optimization since been proven in solving optimization problems without using large memory storage. In this paper, we proposed a new modification of the Hestenes-Stiefel conjugate gradient parameter that fulfils the condition of sufficient descent using a strong Wolfe-Powell line search. Besides, the conjugate gradient method with the proposed conjugate gradient also guarantees low computation of iteration and CPU time by comparing with other classical conjugate gradient parameters. Numerical results have shown that the conjugate gradient method with the proposed conjugate gradient parameter performed better than the conjugate gradient method with other classical conjugate gradient parameters. 2021 Conference or Workshop Item PeerReviewed text en http://eprints.uthm.edu.my/2643/1/P12682_fab91575b27daa5c82a8d41786ab381e.pdf Japri, Nur Athira and Basri, Srimazzura and Mamat, Mustafa (2021) New modification of the hestenes-stiefel with strong wolfe line search. In: SCIEMATHIC 2020, 1-2 December 2020, UTHM. https://doi.org/10.1063/5.0053211 Published |
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QC Physics Japri, Nur Athira Basri, Srimazzura Mamat, Mustafa New modification of the hestenes-stiefel with strong wolfe line search |
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. The method of the nonlinear conjugate gradient is widely used in solving large-scale unconstrained optimization since been proven in solving optimization problems without using large memory storage. In this paper, we proposed a new modification of the Hestenes-Stiefel conjugate gradient parameter that fulfils the condition of sufficient descent using a strong Wolfe-Powell line search. Besides, the conjugate gradient method with the proposed conjugate gradient also guarantees low computation of iteration and CPU time by comparing with other classical conjugate gradient parameters. Numerical results have shown that the conjugate gradient method with the proposed conjugate gradient parameter performed better than the conjugate gradient method with other classical conjugate gradient parameters. |
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Conference or Workshop Item |
author |
Japri, Nur Athira Basri, Srimazzura Mamat, Mustafa |
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Japri, Nur Athira Basri, Srimazzura Mamat, Mustafa |
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Japri, Nur Athira |
title |
New modification of the hestenes-stiefel with strong wolfe line search |
title_short |
New modification of the hestenes-stiefel with strong wolfe line search |
title_full |
New modification of the hestenes-stiefel with strong wolfe line search |
title_fullStr |
New modification of the hestenes-stiefel with strong wolfe line search |
title_full_unstemmed |
New modification of the hestenes-stiefel with strong wolfe line search |
title_sort |
new modification of the hestenes-stiefel with strong wolfe line search |
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2021 |
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http://eprints.uthm.edu.my/2643/1/P12682_fab91575b27daa5c82a8d41786ab381e.pdf http://eprints.uthm.edu.my/2643/ https://doi.org/10.1063/5.0053211 Published |
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1738581017069879296 |