Scalar Parameter of a Spectral PRP Conjugate Gradient Method for Unconstrained optimization


  • Usman A Yakubu Department of Mathematics, Northwest University, Kano, Nigeria
  • Abdul Iguda Department of Mathematical Sciences, Bayero University Kano, Nigeria
  • Abba V Mandara Department of Mathematics, University of Maiduguri, Borno, Nigeria
  • Salisu Murtala Department of Mathematics, Federal University Dutse, Jigawa, Nigeria



Sufficient descent property; exact line search; spectral CG; global convergence.


In recent times, conjugate gradient method (CG) have been broadly used to solve nonlinear unconstrained minimization problems as a result of fewer storage locations and computational expensive in dealing with large-scale problems. In this work, we present a spectral PRP CG method which derived from the CG search direction without secant condition and utilized some of the benchmark test problem functions with several variables to prove its global convergence properties and satisfies sufficient descent condition, the results are validated by exact line search techniques.