ANOTHER HYBRID CONJUGATE GRADIENT METHOD FOR UNCONSTRAINED OPTIMIZATION PROBLEMS

Authors

  • M. KOONTSE University of Botswana, Department of Mathematics, Private Bag UB00704, Gaborone, Botswana
  • P. KAELO University of Botswana, Department of Mathematics, Private Bag UB00704, Gaborone, Botswana

Keywords:

hybrid Conjugate Gradient, line search, Convergence analysis

Abstract

Conjugate gradient method is one of the most useful method for solving large scale unconstrained optimization problems. In this article a new hybrid conjugate gradient method that satisfies the descent condition independently of the line searches is proposed. In particular, it is a hybrid of the Fletcher-Reeves~($\beta_k^{FR}$) and Polak-Ribiere-Polyak~($\beta_k^{PRP}$) methods. Convergence analysis of the new method is presented. Numerical results of the method show that the proposed hybrid algorithm is just as competitive.

Author Biography

P. KAELO, University of Botswana, Department of Mathematics, Private Bag UB00704, Gaborone, Botswana

Lecturer at Department of Mathematics, University of Botswana.

Additional Files

Published

01/28/2015

Issue

Vol. 5 No. 2 (2014): JNAO

Section

Research Articles

License

Copyright (c) 2024 Journal of Nonlinear Analysis and Optimization: Theory & Applications (JNAO)

Creative Commons License

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Copyright (c) 2010 Journal of Nonlinear Analysis and Optimization: Theory & Applications

Creative Commons License

This work is licensed under aย Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.