Modification on Spectral Conjugate Gradient Method for Unconstrained Optimization

  • Authors

    • Usman Abbas Yakubu
    • Mustafa Mamat
    • Mohamad Afendee Mohamed
    • Sukono .
    • Mohd Rivaie
    https://doi.org/10.14419/ijet.v7i3.28.23466
  • Global convergence, inexact line search, spectral CG, secant condition, sufficient descent property.

  • Abstract

    The classical Newton’s direction and spectral conjugate gradient direction are the prominent directions in solving large-scale unconstrained optimization problems. Using the standard secant equation, a modified spectral CG method (MSCG) is proposed, the scheme is a modification of Birgin and Martinez spectral CG method (SCG). Sufficient descent property as well as global convergence has been proved by strong Wolfe line search. Numerical outcome shows that the method is practically effective when compared with classical PRP, FR and spectral CG methods.

                                                                                                                                          

     

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  • How to Cite

    Abbas Yakubu, U., Mamat, M., Afendee Mohamed, M., ., S., & Rivaie, M. (2018). Modification on Spectral Conjugate Gradient Method for Unconstrained Optimization. International Journal of Engineering & Technology, 7(3.28), 307-311. https://doi.org/10.14419/ijet.v7i3.28.23466

    Received date: 2018-12-08

    Accepted date: 2018-12-08