Mohamed Ahmed Hamoda

@asmarya.edu.ly

Department of Mathematica / Faculty of Sciences
Alasmarya Islamic University

Mohamed Ahmed Hamoda


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https://researchid.co/hamoda

RESEARCH INTERESTS

Optimization
6

Scopus Publications

99

Scholar Citations

5

Scholar h-index

3

Scholar i10-index

Scopus Publications

  • The convergence properties of new hybrid conjugate gradient method
    Y Salih, M A Hamoda, Sukono, M Mamat
    Iop Conference Series Materials Science and Engineering, 2019
    In this paper, a new Hybrid Conjugate Gradient Methods is presented, which produced sufficient descent search direction at every iteration and global Convergence Properties for solving large-scale nonlinear optimization problem under exact line search. The numerical experiments show that a hybrid method has the best efficiency for the test problems.
  • A conjugate gradient method with Strong Wolfe-Powell line search for unconstrained optimization
    Mohamed Hamoda, Mustafa Mamat, Mohd Rivaie, Zabidin Salleh
    Applied Mathematical Sciences, 2016
    In this paper, a modified conjugate gradient method is presented for solving large-scale unconstrained optimization problems, which possesses the sufficient descent property with Strong Wolfe-Powell line search. A global convergence result was proved when the (SWP) line search was used under some conditions. Computational results for a set consisting of 138 unconstrained optimization test problems showed that this new conjugate gradient algorithm seems to converge more stable and is superior to other similar methods in many situations.
  • A comparative study of three new conjugate gradient methods with exact line search
    Mohamed Hamoda, Mohd Rivaie, Abdelrhaman Abshar, Mustafa Mamat
    Aip Conference Proceedings, 2015
    Conjugate Gradient methods play an important role in solving unconstrained optimization, especially for large scale problems. In this paper, we compared the performance profile of the classical conjugate gradient coefficients FR, PRP with three new βk. These three new βk possess global convergence properties using the exact line search. Preliminary numerical results show that the three new βk are very promising and efficient when compared to CG coefficients FR, PRP.
  • A conjugate gradient method with inexact line search for unconstrained optimization
    Mohamed Hamoda, Mohd Rivaie, Mustafa Mamat, Zabidin Salleh
    Applied Mathematical Sciences, 2015
    In this paper, an efficient nonlinear modified PRP conjugate gradient method is presented for solving large-scale unconstrained optimization problems. The sufficient descent property is satisfied under strong Wolfe-Powell (SWP) line search by restricting the parameter 4 / 1   . The global convergence result is established under the (SWP) line search conditions. Numerical results, for a set consisting of 133 unconstrained optimization test problems, show that this method is better than the PRP method and the FR method.
  • A comparative study of two new conjugate gradient methods
    Mohamed Hamoda, Abdelrhaman Abashar, Mustafa Mamat, Mohd Rivaie
    Aip Conference Proceedings, 2015
    In this paper, we compared the performance profile of the classical conjugate gradient coefficients FR, PRP with two new βk. These two new βk possess global convergence properties using the exact line search. Preliminary numerical results show that, the two new βk is very promising and efficient when compared to CG coefficients FR, PRP.
  • A new nonlinear conjugate gradient coefficient for unconstrained optimization
    Mohamed Hamoda, Mohd Rivaie, Mustafa Mamat, Zabidin Salleh
    Applied Mathematical Sciences, 2015
    In this paper, we suggest a new nonlinear conjugate gradient method for solving large scale unconstrained optimization problems. We prove that the new conjugate gradient coefficient k β with exact line search is globally convergent. Preliminary numerical results with a set of 116 unconstrained optimization problems show that k β is very promising and efficient when compared to the other conjugate gradient coefficients Fletcher Reeves ) (FR and Polak -Ribiere – Polyak ) (PRP .

RECENT SCHOLAR PUBLICATIONS

  • The convergence properties of new hybrid conjugate gradient method
    Y Salih, MA Hamoda, Sukono, M Mamat
    IOP Conference Series: Materials Science and Engineering 567 (1), 012031 , 2019
    2019
    Citations: 4
  • AN EFFICIENT PRP-HRM HYBRID CONJUGATE GRADIENT METHOD FOR SOLVING UNCONSTRAINED OPTIMIZATION
    MA Hamoda, M Rivaie, M Mamat
    Journal of Humanities and Applied Science 32, 99-114 , 2019
    2019
  • New Hybrid Conjugate Gradient Method with Global Convergence Properties for Unconstrained Optimization
    Y Salih, MA Hamoda, M Rivaie
    Malaysian Journal of computing and applied mathematics (MyJCAM) 1 (1), 29-38 , 2018
    2018
    Citations: 17
  • A comparative study of two new conjugate gradient methods
    M Hamoda, A Abashar, M Mamat, M Rivaie
    2017
    Citations: 6
  • A NEW NONLINEAR CONJUGATE GRADIENT METHOD WITH EXACT LINE SEARCH FOR UNCONSTRAINED OPTIMIZATION
    MA Hamoda, M Rivaie, M Mamat
    Journal of Humanities and Applied Science (JHAS), 1-16 , 2017
    2017
    Citations: 4
  • Modification of Polak-Ribiere-Polyak (PRP) Conjugate Gradient Coefficient for Unconstrained Optimization Problems
    M Hamoda
    2016
  • A conjugate gradient method with strong Wolfe-Powell line search for unconstrained optimization
    M Hamoda, M Mamat, M Rivaie, Z Salleh
    Appl. Math. Sci 10, 721-734 , 2016
    2016
    Citations: 48
  • A comparative study of three new conjugate gradient methods with exact line search
    M Hamoda, M Rivaie, A Abshar, M Mamat
    AIP Conference Proceedings 1682 (1), 020030 , 2015
    2015
  • A Conjugate Gradient Method with Inexact Line Search for Unconstrained Optimization
    Mohamed Hamoda, Mohd Rivaie, Mustafa Mamat, Zabidin Salleh
    Applied Mathematical Sciences 9 (37), 1823-1832 , 2015
    2015
    Citations: 7
  • A New Nonlinear Conjugate Gradient Coefficient for Unconstrained Optimization
    Mohamed Hamoda, Mohd Rivaie ,Mustafa Mamat, Zabidin Salleh
    Applied Mathematical Sciences 9 (37), 1813-1822 , 2015
    2015
    Citations: 13

MOST CITED SCHOLAR PUBLICATIONS

  • A conjugate gradient method with strong Wolfe-Powell line search for unconstrained optimization
    M Hamoda, M Mamat, M Rivaie, Z Salleh
    Appl. Math. Sci 10, 721-734 , 2016
    2016
    Citations: 48
  • New Hybrid Conjugate Gradient Method with Global Convergence Properties for Unconstrained Optimization
    Y Salih, MA Hamoda, M Rivaie
    Malaysian Journal of computing and applied mathematics (MyJCAM) 1 (1), 29-38 , 2018
    2018
    Citations: 17
  • A New Nonlinear Conjugate Gradient Coefficient for Unconstrained Optimization
    Mohamed Hamoda, Mohd Rivaie ,Mustafa Mamat, Zabidin Salleh
    Applied Mathematical Sciences 9 (37), 1813-1822 , 2015
    2015
    Citations: 13
  • A Conjugate Gradient Method with Inexact Line Search for Unconstrained Optimization
    Mohamed Hamoda, Mohd Rivaie, Mustafa Mamat, Zabidin Salleh
    Applied Mathematical Sciences 9 (37), 1823-1832 , 2015
    2015
    Citations: 7
  • A comparative study of two new conjugate gradient methods
    M Hamoda, A Abashar, M Mamat, M Rivaie
    2017
    Citations: 6
  • The convergence properties of new hybrid conjugate gradient method
    Y Salih, MA Hamoda, Sukono, M Mamat
    IOP Conference Series: Materials Science and Engineering 567 (1), 012031 , 2019
    2019
    Citations: 4
  • A NEW NONLINEAR CONJUGATE GRADIENT METHOD WITH EXACT LINE SEARCH FOR UNCONSTRAINED OPTIMIZATION
    MA Hamoda, M Rivaie, M Mamat
    Journal of Humanities and Applied Science (JHAS), 1-16 , 2017
    2017
    Citations: 4
  • AN EFFICIENT PRP-HRM HYBRID CONJUGATE GRADIENT METHOD FOR SOLVING UNCONSTRAINED OPTIMIZATION
    MA Hamoda, M Rivaie, M Mamat
    Journal of Humanities and Applied Science 32, 99-114 , 2019
    2019
  • Modification of Polak-Ribiere-Polyak (PRP) Conjugate Gradient Coefficient for Unconstrained Optimization Problems
    M Hamoda
    2016
  • A comparative study of three new conjugate gradient methods with exact line search
    M Hamoda, M Rivaie, A Abshar, M Mamat
    AIP Conference Proceedings 1682 (1), 020030 , 2015
    2015