A Liu-Storey-type conjugate gradient method for unconstrained minimization problem with application in motion control

Conjugate gradient methods have played a vital role in finding the minimizers of large-scale unconstrained optimization problems due to the simplicity of their iteration, convergence properties and their low memory requirements. Based on the Liu-Storey conjugate gradient method, in this paper, we pr...

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Bibliographic Details
Published in:Journal of King Saud University. Science 2022-06, Vol.34 (4), p.101923, Article 101923
Main Authors: Abubakar, Auwal Bala, Malik, Maulana, Kumam, Poom, Mohammad, Hassan, Sun, Min, Ibrahim, Abdulkarim Hassan, Kiri, Aliyu Ibrahim
Format: Article
Language:English
Subjects:
Conjugate gradient method
Global convergence
Line search
Unconstrained optimization
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Summary:Conjugate gradient methods have played a vital role in finding the minimizers of large-scale unconstrained optimization problems due to the simplicity of their iteration, convergence properties and their low memory requirements. Based on the Liu-Storey conjugate gradient method, in this paper, we present a Liu-Storey type method for finding the minimizers of large-scale unconstrained optimization problems. The direction of the proposed method is constructed in such a way that the sufficient descent condition is satisfied. Furthermore, we establish the global convergence result of the method under the standard Wolfe and Armijo-like line searches. Numerical findings indicate that our presented approach is efficient and robust in solving large-scale test problems. In addition, an application of the method is explored.
ISSN:1018-3647
DOI:10.1016/j.jksus.2022.101923