Volume 56, Number 4, July-August 2022
|Page(s)||2315 - 2327|
|Published online||29 July 2022|
New iterative conjugate gradient method for nonlinear unconstrained optimization
Laboratory Informatics and Mathematics (LiM), Mohamed Cherif Messaadia University, Souk-Ahras, Algeria
* Corresponding author: email@example.com
Accepted: 21 June 2022
Conjugate gradient methods (CG) are an important class of methods for solving unconstrained optimization problems, especially for large-scale problems. Recently, they have been much studied. In this paper, we propose a new conjugate gradient method for unconstrained optimization. This method is a convex combination of Fletcher and Reeves (abbreviated FR), Polak–Ribiere–Polyak (abbreviated PRP) and Dai and Yuan (abbreviated DY) methods. The new conjugate gradient methods with the Wolfe line search is shown to ensure the descent property of each search direction. Some general convergence results are also established for this method. The numerical experiments are done to test the efficiency of the proposed method, which confirms its promising potentials.
Mathematics Subject Classification: 65K05 / 90C25 / 90C26 / 90C27 / 90C30
Key words: Unconstrained optimization / hybrid conjugate gradient method / sufficient descent / convex combination / global convergence
© The authors. Published by EDP Sciences, ROADEF, SMAI 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.