Modified Dai-Yuan Conjugate Gradient Method with Sufficient Descent Property for Nonlinear Equations

Abhiwat Kambheera*, Abdulkarim Hassan Ibrahim, Abubakar Bakoji Muhammad, Auwal Bala Abubakar, Basim A. Hassan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

The convex constraint nonlinear equation problem is to find a point q with the property that q 2 D where D is a nonempty closed convex subset of Euclidean space Rn. The convex constraint problem arises in many practical applications such as chemical equilibrium systems, economic equilibrium problems, and the power flow equations. In this paper, we extend the modified Dai-Yuan nonlinear conjugate gradient method with su ciently descent property proposed for large-scale optimization problem to solve convex constraint nonlinear equation and establish the global convergence of the proposed algorithm under certain mild conditions. Our result is a significant improvement compared with related method for solving the convex constraint nonlinear equation.

Original languageEnglish
Pages (from-to)145-167
Number of pages23
JournalThai Journal of Mathematics
Volume2022
Issue numberSpecial Issue 2022
Publication statusPublished - 2022
Externally publishedYes

Keywords

  • derivative-free method
  • global convergence
  • nonlinear equations
  • projection method

Fingerprint

Dive into the research topics of 'Modified Dai-Yuan Conjugate Gradient Method with Sufficient Descent Property for Nonlinear Equations'. Together they form a unique fingerprint.

Cite this