Application of Spectral PRP Conjugate Gradient Parameter for Unconstrained Optimization Problems

Authors

  • Usman Abbas Yakubu Department of Mathematics, Yusuf Maitama Sule University, Kano, Nigeria
  • Ibrahim Abdullahi Department of Mathematics, Yusuf Maitama Sule University, Kano, Nigeria
  • Salisu Murtala Department of Mathematics, Federal University Dutse, Jigawa, Nigeria
  • Abba V Mandara Department of Mathematics, University of Maiduguri, Borno, Nigeria

DOI:

https://doi.org/10.37231/myjcam.2020.3.2.51

Keywords:

Sufficient Descent Property; Exact Line Search; Spectral CG; Global Convergence; Regression Analysis

Abstract

Conjugate Gradient (CG) method have been utilised to solve nonlinear unconstrained optimization problems because of less storage locations and fewer computational cost in dealing with large-scale problems. In this paper, we present a real life application of spectral PRP Conjugate Gradient method in regression analysis, the proposed method is suitably deriving from the CG search direction without secant condition. Some benchmark functions with several variables have been use to prove the global convergence properties and satisfies sufficient descent condition. The numerical results are certifying by exact line search techniques; the method outperform the prominent least square method

Published

2020-12-05