Comparison of conjugate gradient method on solving unconstrained optimization problems

Maulana, Malik and Mustafa, Mamat and Siti Sabariah, Abas and Ibrahim, Mohammed Sulaiman and Sukono, . and Abdul Talib, Bon (2020) Comparison of conjugate gradient method on solving unconstrained optimization problems. In: 5th North American International Conference on Industrial Engineering and Operations Management, 10-14 Aug 2020, Michigan, USA.

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Abstract

Conjugate gradient (CG) method approaches have been instrumental in solving unconstrained optimization problems. In 2020, Malik et al. have proposed a new hybrid coefficient (H-MS2), a combination of the RMIL coefficient and the new coefficient. In this paper, we propose the new method, which takes the new coefficients from H-MS2. Also, we will compare the new method and some of the classic methods that already based on the number of iterations and central processing unit (CPU) time. The new method fulfills the sufficient descent condition and global convergence properties, and it’s tested on a set functions under exact line search. The numerical results show that the new CG method has the best efficiency between all the methods tested.

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