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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محفوظ في:
التفاصيل البيبلوغرافية
المؤلفون الرئيسيون: Za’aba, Fatin Nadhirah, Marjugi, Siti Mahani
التنسيق: مقال
منشور في: Malaysian Mathematical Science Society 2021
الوصول للمادة أونلاين:http://psasir.upm.edu.my/id/eprint/96474/
https://myjms.mohe.gov.my/index.php/dismath/article/view/15550/7995
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المؤسسة: Universiti Putra Malaysia
الوصف
الملخص: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.