Solving a large scale nonlinear unconstrained optimization problems by using new coefficient of conjugate gradient method with exact line search direction

  • Authors

    • Talat Alkouli
    • Mustafa Mamat
    • Mohd Rivaie
    • Puspa Liza Ghazali
    https://doi.org/10.14419/ijet.v7i3.28.20976

    Received date: October 4, 2018

    Accepted date: October 4, 2018

    Published date: August 17, 2018

  • Conjugate gradient, Exact line search, Global convergence, Sufficient descent condition, Unconstrained optimization.

  • Abstract

    In this paper, an efficient modification of nonlinear conjugate gradient method and an associated implementation, based on an exact line search, are proposed and analyzed to solve large-scale unconstrained optimization problems. The method satisfies the sufficient descent property. Furthermore, global convergence result is proved. Computational results for a set of unconstrained optimization test problems, some of them from CUTE library, showed that this new conjugate gradient algorithm seems to converge more stable and outperforms the other similar methods in many situations.

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  • How to Cite

    Alkouli, T., Mamat, M., Rivaie, M., & Liza Ghazali, P. (2018). Solving a large scale nonlinear unconstrained optimization problems by using new coefficient of conjugate gradient method with exact line search direction. International Journal of Engineering and Technology, 7(3.28), 92-96. https://doi.org/10.14419/ijet.v7i3.28.20976