TY - JOUR
T1 - Comparison of conjugate gradient method on solving unconstrained optimization problems
AU - Malik, Maulana
AU - Mamat, Mustafa
AU - Abas, Siti Sabariah
AU - Sulaiman, Ibrahim Mohammed
AU - Sukono,
AU - Bon, Abdul Talib
N1 - Funding Information:
We would like to thank the reviewer for their suggestions and comments. This work is supported the Ph.D. mathematics study group on optimization field in Faculty of Informatics and Computing, Universiti Sultan Zainal Abidin (UniSZA), Terengganu, Malaysia
Publisher Copyright:
© IEOM Society International.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
KW - Conjugate gradient method
KW - Exact line search
KW - Global convergence properties
KW - Sufficient descent condition
KW - Unconstrained optimization problems
UR - http://www.scopus.com/inward/record.url?scp=85096531199&partnerID=8YFLogxK
M3 - Conference article
AN - SCOPUS:85096531199
SN - 2169-8767
JO - Proceedings of the International Conference on Industrial Engineering and Operations Management
JF - Proceedings of the International Conference on Industrial Engineering and Operations Management
IS - August
T2 - Proceedings of the 5th NA International Conference on Industrial Engineering and Operations Management, IOEM 2020
Y2 - 10 August 2020 through 14 August 2020
ER -