General Letters in Mathematics

Volume 12 - Issue 1 (5) | PP: 40 - 48 Language : English
DOI : https://doi.org/10.31559/glm2022.12.1.5
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Conjugated Gradient with Four Terms for Nonlinear Unconstrained Optimization

Ahmed Anwer Mustafa
Received Date Revised Date Accepted Date Publication Date
22/1/2022 5/3/2022 16/3/2022 18/5/2022
Abstract
The nonlinear conjugate gradient (GJG) technique is an effective tool for addressing minimization on a huge scale. It can be used in a variety of applications., We presented a novel conjugate gradient approach based on two hypotheses, and we equalized the two hypotheses and retrieved the good parameter in this article. To get a new conjugated gradient, we multiplied the new parameter by a control parameter and substituted it in the second equation. a fresh equation for 𝛽𝑘 is proposed. It has global convergence qualities. When compared to the two most common conjugate gradient techniques, our algorithm outperforms them in terms of both the number of iterations (NOIS) and the number of functions (NOFS). The new technique is efficient in real computing and superior to previous comparable approaches in many instances, according to numerical results.


How To Cite This Article
Mustafa , A. A. (2022). Conjugated Gradient with Four Terms for Nonlinear Unconstrained Optimization. General Letters in Mathematics, 12 (1), 40-48, 10.31559/glm2022.12.1.5

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