A modified conjugate gradient coefficient under exact line search for unconstrained optimization

  • Authors

    • Nurul Aini
    • Nurul Hajar
    • Mohd Rivaie
    • Mustafa Mamat
    2018-08-17
    https://doi.org/10.14419/ijet.v7i3.28.20973
  • Conjugate gradient method, unconstrained optimization, sufficient descent, global convergence, exact line search.

  • Abstract

    The conjugate gradient (CG) method is a well-known solver for large-scale unconstrained optimization problems. In this paper, a modified CG method based on AMR* and CD method is presented. The resulting algorithm for the new CG method is proved to be globally convergent under exact line search both under some mild conditions. Comparisons of numerical performance are made involving the new method and four other CG methods. The results show that the proposed method is more efficient.

     

     

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  • How to Cite

    Aini, N., Hajar, N., Rivaie, M., & Mamat, M. (2018). A modified conjugate gradient coefficient under exact line search for unconstrained optimization. International Journal of Engineering & Technology, 7(3.28), 84-88. https://doi.org/10.14419/ijet.v7i3.28.20973

    Received date: 2018-10-04

    Accepted date: 2018-10-04

    Published date: 2018-08-17