Open AccessA comparison on classical-hybrid conjugate gradient method under exact line search
Author(s) -
Nur Syarafina Mohamed,
Mustafa Mamat,
Mohd Rivaie,
Shazlyn Milleana Shaharudin
Publication year - 2019
Publication title -
ijain (international journal of advances in intelligent informatics)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.183
H-Index - 9
eISSN - 2548-3161
pISSN - 2442-6571
DOI - 10.26555/ijain.v5i2.356
Subject(s) - conjugate gradient method , line search , computer science , conjugate , line (geometry) , algorithm , convex combination , regular polygon , mathematics , convex optimization , mathematical analysis , geometry , computer security , radius
One of the popular approaches in modifying the Conjugate Gradient (CG) Method is hybridization. In this paper, a new hybrid CG is introduced and its performance is compared to the classical CG method which are Rivaie-Mustafa-Ismail-Leong (RMIL) and Syarafina-Mustafa-Rivaie (SMR) methods. The proposed hybrid CG is evaluated as a convex combination of RMIL and SMR method. Their performance are analyzed under the exact line search. The comparison performance showed that the hybrid CG is promising and has outperformed the classical CG of RMIL and SMR in terms of the number of iterations and central processing unit per time.