A New Hybrid Conjugates Gradient Algorithm for Unconstraint Optimization Problems
Abstract
In this paper, we present a new hybrid conjugate gradient strategy that is both efficient and effective for solving unconstrained optimization problems. The parameter is derived from a convex combination of the and the conjugate gradient methods. We demonstrated that this strategy is globally convergent under strong Wolfe line search conditions, and that the recommended hybrid CG method is capable of creating a descending search direction at each iteration. Numerical results are presented in this study, demonstrating that the proposed technique is both efficient and promising.
Copyright (c) 2022 Basma Tareq
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Copyright Notice
The Authors submitting a manuscript do so on the understanding that if accepted for publication, copyright of the article shall be assigned to journal IJETS, University Of Technology Yogyakarta as publisher of the journal, and the author also holds the copyright without restriction.
Copyright encompasses exclusive rights to reproduce and deliver the article in all form and media, including reprints, photographs, microfilms and any other similar reproductions, as well as translations. The reproduction of any part of this journal, its storage in databases and its transmission by any form or media, such as electronic, electrostatic and mechanical copies, photocopies, recordings, magnetic media, etc. , are allowed with a written permission from journal IJETS, University Of Technology Yogyakarta.
Jurnal IJETS Board, University Of Technology Yogyakarta, the Editors and the Advisory International Editorial Board make every effort to ensure that no wrong or misleading data, opinions or statements be published in the journal. In any way, the contents of the articles and advertisements published in the journal IJETS, University Of Technology Yogyakarta are sole and exclusive responsibility of their respective authors and advertisers.
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0