Comparison of the AIM conjugate gradient method under exact and inexact line search for solving unconstrained optimization problems
The nonlinear conjugate gradient (CG) method is essential in solving large-scale unconstrained optimization problems due to its simplicity and low memory requirement. Numerous studies and improvements have been made recently to improve this strategy. Hence, this study will create a modified CG metho...
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| Format: | Article |
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Malaysian Mathematical Science Society
2021
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| _version_ | 1796983245105004544 |
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| author | Za’aba, Fatin Nadhirah Marjugi, Siti Mahani |
| author_facet | Za’aba, Fatin Nadhirah Marjugi, Siti Mahani |
| author_sort | Za’aba, Fatin Nadhirah |
| collection | UPM |
| description | The nonlinear conjugate gradient (CG) method is essential in solving large-scale unconstrained optimization problems due to its simplicity and low memory requirement. Numerous studies and improvements have been made recently to improve this strategy. Hence, this study will create a modified CG method with inexact line search, Strong Wolfe-Powell conditions. The global convergence and sufficient descent properties are established by using an inexact line search. The numerical result demonstrates that the modified method with inexact line search is superior and more efficient when compared to other CG methods. |
| first_indexed | 2024-03-06T11:03:46Z |
| format | Article |
| id | upm.eprints-96474 |
| institution | Universiti Putra Malaysia |
| last_indexed | 2024-03-06T11:03:46Z |
| publishDate | 2021 |
| publisher | Malaysian Mathematical Science Society |
| record_format | dspace |
| spelling | upm.eprints-964742023-01-11T09:06:08Z http://psasir.upm.edu.my/id/eprint/96474/ Comparison of the AIM conjugate gradient method under exact and inexact line search for solving unconstrained optimization problems Za’aba, Fatin Nadhirah Marjugi, Siti Mahani The nonlinear conjugate gradient (CG) method is essential in solving large-scale unconstrained optimization problems due to its simplicity and low memory requirement. Numerous studies and improvements have been made recently to improve this strategy. Hence, this study will create a modified CG method with inexact line search, Strong Wolfe-Powell conditions. The global convergence and sufficient descent properties are established by using an inexact line search. The numerical result demonstrates that the modified method with inexact line search is superior and more efficient when compared to other CG methods. Malaysian Mathematical Science Society 2021 Article PeerReviewed Za’aba, Fatin Nadhirah and Marjugi, Siti Mahani (2021) Comparison of the AIM conjugate gradient method under exact and inexact line search for solving unconstrained optimization problems. Discovering Mathematics, 43 (2). 101 - 110. ISSN 2231-7023 https://myjms.mohe.gov.my/index.php/dismath/article/view/15550/7995 |
| spellingShingle | Za’aba, Fatin Nadhirah Marjugi, Siti Mahani Comparison of the AIM conjugate gradient method under exact and inexact line search for solving unconstrained optimization problems |
| title | Comparison of the AIM conjugate gradient method under exact and inexact line search for solving unconstrained optimization problems |
| title_full | Comparison of the AIM conjugate gradient method under exact and inexact line search for solving unconstrained optimization problems |
| title_fullStr | Comparison of the AIM conjugate gradient method under exact and inexact line search for solving unconstrained optimization problems |
| title_full_unstemmed | Comparison of the AIM conjugate gradient method under exact and inexact line search for solving unconstrained optimization problems |
| title_short | Comparison of the AIM conjugate gradient method under exact and inexact line search for solving unconstrained optimization problems |
| title_sort | comparison of the aim conjugate gradient method under exact and inexact line search for solving unconstrained optimization problems |
| work_keys_str_mv | AT zaabafatinnadhirah comparisonoftheaimconjugategradientmethodunderexactandinexactlinesearchforsolvingunconstrainedoptimizationproblems AT marjugisitimahani comparisonoftheaimconjugategradientmethodunderexactandinexactlinesearchforsolvingunconstrainedoptimizationproblems |