The convergence properties of a new hybrid conjugate gradient parameter for unconstrained optimization models

I. M. Sulaiman, M. Mamat, M. Y. Waziri, U. A. Yakubu, M. Malik

Research output: Contribution to journalConference articlepeer-review

1 Citation (Scopus)

Abstract

The hybrid conjugate gradient (CG) algorithms are among the efficient modifications of the conjugate gradient methods. Some interesting features of the hybrid modifications include inherenting the nice convergence properties and efficient numerical performance of the existing CG methods. In this paper, we proposed a new hybrid CG algorithm that inherits the features of the Rivaie et al. (RMIL∗) and Dai (RMIL+) conjugate gradient methods. The proposed algorithm generates a descent direction under the strong Wolfe line search conditions. Preliminary results on some benchmark problems reveal that the proposed method efficient and promising.

Original languageEnglish
Article number012012
JournalJournal of Physics: Conference Series
Volume1734
Issue number1
DOIs
Publication statusPublished - 4 Jan 2021
Event1st International Conference on Recent Trends in Applied Research, ICoRTAR 2020 - Virtual, Online, Nigeria
Duration: 14 Aug 202015 Aug 2020

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