Comparison of conjugate gradient method on solving unconstrained optimization problems

Maulana Malik, Mustafa Mamat, Siti Sabariah Abas, Ibrahim Mohammed Sulaiman, Sukono, Abdul Talib Bon

Research output: Contribution to journalConference articlepeer-review

1 Citation (Scopus)

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.

Original languageEnglish
JournalProceedings of the International Conference on Industrial Engineering and Operations Management
Issue numberAugust
Publication statusPublished - 2020
EventProceedings of the 5th NA International Conference on Industrial Engineering and Operations Management, IOEM 2020 - Virtual, United States
Duration: 10 Aug 202014 Aug 2020

Keywords

  • Conjugate gradient method
  • Exact line search
  • Global convergence properties
  • Sufficient descent condition
  • Unconstrained optimization problems

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