A Liu-Storey-type conjugate gradient method for unconstrained minimization problem with application in motion control

Auwal Bala Abubakar, Maulana Malik, Poom Kumam, Hassan Mohammad, Min Sun, Abdulkarim Hassan Ibrahim, Aliyu Ibrahim Kiri

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Conjugate gradient methods have played a vital role in finding the minimizers of large-scale unconstrained optimization problems due to the simplicity of their iteration, convergence properties and their low memory requirements. Based on the Liu-Storey conjugate gradient method, in this paper, we present a Liu-Storey type method for finding the minimizers of large-scale unconstrained optimization problems. The direction of the proposed method is constructed in such a way that the sufficient descent condition is satisfied. Furthermore, we establish the global convergence result of the method under the standard Wolfe and Armijo-like line searches. Numerical findings indicate that our presented approach is efficient and robust in solving large-scale test problems. In addition, an application of the method is explored.

Original languageEnglish
Article number101923
JournalJournal of King Saud University - Science
Volume34
Issue number4
DOIs
Publication statusPublished - Jun 2022

Keywords

  • Conjugate gradient method
  • Global convergence
  • Line search
  • Unconstrained optimization

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