TY - JOUR
T1 - A hybrid HS-LS conjugate gradient algorithm for unconstrained optimization with applications in motion control and image recovery
AU - Kumam, Poom
AU - Abubakar, Auwal Bala
AU - Malik, Maulana
AU - Ibrahim, Abdulkarim Hassan
AU - Pakkaranang, Nuttapol
AU - Panyanak, Bancha
N1 - Funding Information:
The second author acknowledge with thanks, the Department of Mathematics and Applied Mathematics at the Sefako Makgatho Health Sciences University, Thailand. The fifth author was partially supported by Phetchabun Rajabhat University, Thailand and Thailand Science Research and Innovation (grant number 182093). The sixth author was partially supported by Chiang Mai University, Thailand and the NSRF via the Program Management Unit for Human Resources and Institutional Development, Research and Innovation, Thailand (grant number B05F640183). Moreover, this project is funded by National Research Council of Thailand (NRCT) under Research Grants for Talented Mid-Career Researchers (Contract no. N41A640089).
Funding Information:
The second author acknowledge with thanks, the Department of Mathematics and Applied Mathematics at the Sefako Makgatho Health Sciences University, Thailand . The fifth author was partially supported by Phetchabun Rajabhat University, Thailand and Thailand Science Research and Innovation (grant number 182093) . The sixth author was partially supported by Chiang Mai University, Thailand and the NSRF via the Program Management Unit for Human Resources and Institutional Development, Research and Innovation, Thailand (grant number B05F640183 ). Moreover, this project is funded by National Research Council of Thailand (NRCT) under Research Grants for Talented Mid-Career Researchers (Contract no. N41A640089 ).
Publisher Copyright:
© 2023 Elsevier B.V.
PY - 2023/12/1
Y1 - 2023/12/1
N2 - This article presents a new hybrid conjugate gradient (CG) algorithm for solving unconstrained optimization problem. The search direction is defined as a combination of Hestenes–Stiefel (HS) and the Liu–Storey (LS) CG parameters and is close to the direction of the memoryless Broyden–Fletcher–Goldferb–Shanno (BFGS) quasi-Newton direction. In addition, the search direction is descent and bounded. The global convergence of the algorithm is obtained under the Wolfe-type and Armijo-type line searches. Numerical experiments on some benchmark test problems is carried out to depict the efficiency and robustness of the hybrid algorithm. Furthermore, a practical application of the algorithm in motion control of robot manipulator and image restoration is provided.
AB - This article presents a new hybrid conjugate gradient (CG) algorithm for solving unconstrained optimization problem. The search direction is defined as a combination of Hestenes–Stiefel (HS) and the Liu–Storey (LS) CG parameters and is close to the direction of the memoryless Broyden–Fletcher–Goldferb–Shanno (BFGS) quasi-Newton direction. In addition, the search direction is descent and bounded. The global convergence of the algorithm is obtained under the Wolfe-type and Armijo-type line searches. Numerical experiments on some benchmark test problems is carried out to depict the efficiency and robustness of the hybrid algorithm. Furthermore, a practical application of the algorithm in motion control of robot manipulator and image restoration is provided.
KW - Global convergence
KW - Line search
KW - Three-term conjugate gradient method
KW - Unconstrained optimization
UR - http://www.scopus.com/inward/record.url?scp=85159468413&partnerID=8YFLogxK
U2 - 10.1016/j.cam.2023.115304
DO - 10.1016/j.cam.2023.115304
M3 - Article
AN - SCOPUS:85159468413
SN - 0377-0427
VL - 433
JO - Journal of Computational and Applied Mathematics
JF - Journal of Computational and Applied Mathematics
M1 - 115304
ER -