Open AccessA new hyhbrid coefficient of conjugate gradient method
Author(s) -
Nur Syarafina Mohamed,
Mustafa Mamat,
Mohd Rivaie,
Shazlyn Milleana Shaharudin
Publication year - 2020
Publication title -
indonesian journal of electrical engineering and computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.241
H-Index - 17
eISSN - 2502-4760
pISSN - 2502-4752
DOI - 10.11591/ijeecs.v18.i3.pp1454-1463
Subject(s) - conjugate gradient method , conjugate , mathematics , convergence (economics) , algorithm , gradient method , gradient descent , computer science , mathematical analysis , artificial intelligence , artificial neural network , economics , economic growth
Hybridization is one of the popular approaches in modifying the conjugate gradient method. In this paper, a new hybrid conjugate gradient is suggested and analyzed in which the parameter
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is evaluated as a convex combination of
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while using exact line search. The proposed method is shown to possess both sufficient descent and global convergence properties. Numerical performances show that the proposed method is promising and has overpowered other hybrid conjugate gradient methods in its number of iterations and central processing unit per time.