GLOBAL CONVERGENCE ANALYSIS OF A MODIFIED CONJUGATE GRADIENT METHOD FOR UNCONSTRAINED OPTIMIZATION PROBLEMS

Authors

  • Omachi Eleojo Alilu
    Federal College of Education, Jama'are, Bauchi State.
  • Abdullahi Ibrahim
    Department of Mathematics, Federal University Dutse (FUD), Jigawa State
  • Sani Usman
    Department of Mathematics, Federal University Dutse (FUD), Jigawa State

Keywords:

Optimization, Coefficient, Algorithm, Descent, Convergence

Abstract

In this paper, the global convergence analysis of a modified conjugate gradient method for solving unconstrained optimization problems was considered. We proposed a modified conjugate gradient method for solving unconstrained optimization problems that incorporates an adaptive step size selection scheme. We analyze the method’s global convergence properties theoretically, demonstrating that it satisfies the sufficient descent and global convergence conditions under various assumptions. And we provide numerical experiments to illustrate its effectiveness and efficiency in solving unconstrained optimization problems. We also compare the numerical performance of the proposed method against three existing methods namely, FR, HS and PR using MATLAB simulations. The proposed method was found to perform better than FR and HS, and in competition with PR with respect to computation time, number of iteration and function evaluation.

Dimensions

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Published

14-12-2024

How to Cite

GLOBAL CONVERGENCE ANALYSIS OF A MODIFIED CONJUGATE GRADIENT METHOD FOR UNCONSTRAINED OPTIMIZATION PROBLEMS. (2024). FUDMA JOURNAL OF SCIENCES, 8(6), 306-312. https://doi.org/10.33003/fjs-2024-0806-2942

Issue

Vol. 8 No. 6 (2024): FUDMA Journal of Sciences - Vol. 8 No. 6

Section

Research Articles
Copyright & Licensing

FUDMA Journal of Sciences

How to Cite

GLOBAL CONVERGENCE ANALYSIS OF A MODIFIED CONJUGATE GRADIENT METHOD FOR UNCONSTRAINED OPTIMIZATION PROBLEMS. (2024). FUDMA JOURNAL OF SCIENCES, 8(6), 306-312. https://doi.org/10.33003/fjs-2024-0806-2942

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