TY - JOUR
T1 - A Liu-Storey-type conjugate gradient method for unconstrained minimization problem with application in motion control
AU - Abubakar, Auwal Bala
AU - Malik, Maulana
AU - Kumam, Poom
AU - Mohammad, Hassan
AU - Sun, Min
AU - Ibrahim, Abdulkarim Hassan
AU - Kiri, Aliyu Ibrahim
N1 - Funding Information:
The authors acknowledge the financial support provided by the Center of Excellence in Theoretical and Computational Science (TaCS-CoE), KMUTT. Also, the (first) author, (Dr. Auwal Bala Abubakar) would like to thank the Postdoctoral Fellowship from King Mongkut’s University of Technology Thonburi (KMUTT), Thailand. Moreover, this project is funded by National Research Council of Thailand (NRCT) under Research Grants for Talented Mid-Career Researchers ( Contract no. N41A640089). Also, the first author acknowledge with thanks, the Department of Mathematics and Applied Mathematics at the Sefako Makgatho Health Sciences University.
Funding Information:
The authors acknowledge the financial support provided by the Center of Excellence in Theoretical and Computational Science (TaCS-CoE), KMUTT. Also, the (first) author, (Dr. Auwal Bala Abubakar) would like to thank the Postdoctoral Fellowship from King Mongkut's University of Technology Thonburi (KMUTT), Thailand. Moreover, this project is funded by National Research Council of Thailand (NRCT) under Research Grants for Talented Mid-Career Researchers (Contract no. N41A640089). Also, the first author acknowledge with thanks, the Department of Mathematics and Applied Mathematics at the Sefako Makgatho Health Sciences University.
Publisher Copyright:
© 2022 The Author(s)
PY - 2022/6
Y1 - 2022/6
N2 - 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.
AB - 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.
KW - Conjugate gradient method
KW - Global convergence
KW - Line search
KW - Unconstrained optimization
UR - http://www.scopus.com/inward/record.url?scp=85125725447&partnerID=8YFLogxK
U2 - 10.1016/j.jksus.2022.101923
DO - 10.1016/j.jksus.2022.101923
M3 - Article
AN - SCOPUS:85125725447
VL - 34
JO - Journal of King Saud University - Science
JF - Journal of King Saud University - Science
SN - 1018-3647
IS - 4
M1 - 101923
ER -