Convergence analysis of a new coefficient conjugate gradient method under exact line search

Maulana Malik, Mustafa Mamat, Siti Sabariah Abas, Sukono

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

Conjugate gradient (CG) methods were instrumental in solving unconstrained, wide-ranging optimization. In this paper, we propose a new CG coefficient family, which holds conditions of sufficient descent and global convergence properties. Under exact line search this new CG is evaluated on a set of functions. Based on number of iterations (NOI) and central processing unit (CPU) time, it then compared its output with that of some of the well-known previous CG methods. The results show that of all the methods tested, the latest CG method has the best performance.

Original languageEnglish
Pages (from-to)187-198
Number of pages12
JournalInternational Journal of Advanced Science and Technology
Volume29
Issue number5
Publication statusPublished - 10 Apr 2020

Keywords

  • Conjugate Gradient Coefficient
  • Conjugate Gradient Method
  • Exact Line Search
  • Global Convergence
  • Sufficient Descent

Fingerprint Dive into the research topics of 'Convergence analysis of a new coefficient conjugate gradient method under exact line search'. Together they form a unique fingerprint.

Cite this