[
A. B. Abubakar, P. Kumam, M. Malik, P. Chaipunya and A. H. Ibrahim, A hybrid FR-DY conjugate gradient algorithm for unconstrained optimization with application in portfolio selection. AIMS Math, 6(6) (2021), 6506-6527.
]Search in Google Scholar
[
O. J. Adeleke, M. O. Olusanya and I. A. Osinuga, A PRP-HS Type Hybrid Nonlinear Conjugate Gradient Method for Solving Unconstrained Optimization Problems, In: Silhavy, R., Silhavy, P., Prokopova, Z (eds) Intelligent Systems Applications in Software Engineering. CoMeSySo 2019 (2019). Advances in Intelligent Systems and Computing, 1046, Springer, Cham.
]Search in Google Scholar
[
A. Alhawarat, M. Mamat, M. Rivaie and Z. Salleh, An efficient hybrid conjugate gradient method with the strong Wolfe-Powell line search, Math. Probl. Eng., 2015: 103517 (2015).
]Search in Google Scholar
[
N. Andrei, An unconstrained optimization test functions collection, Adv. Model. Optim., 10(1) (2008), 147–161.
]Search in Google Scholar
[
A. M. Awwal, I. M. Sulaiman, M. Malik, M. Mamat, P. Kumam and K. Sitthithakerngkiet, A spectral RMIL+ conjugate gradient method for unconstrained optimization with applications in portfolio selection and motion control. IEEE Access, 9 (2021), 75398-75414.
]Search in Google Scholar
[
M. C. Bartholomew-Biggs, Nonlinear Optimization with Financial Applications. Kluwer Academic Publishers, Boston (2006).
]Search in Google Scholar
[
M. C. Bartholomew-Biggs and S. J. Kane, A global optimization problem in portfolio selection. Comput. Manag. Sci., 6 (2009) 329-345.
]Search in Google Scholar
[
Y. H. Dai, A family of hybrid conjugate gradient methods for unconstrained optimization, Math. Comput., 72(243) (2003), 1317-1328.
]Search in Google Scholar
[
Y. H. Dai and L. Liao, New conjugacy conditions and related nonlinear conjugate gradient methods, Appl. Math. Optim., 43 (2001), 87-101.
]Search in Google Scholar
[
Z. Dai and F. Wen, Another improved Wei-Yao-Liu nonlinear conjugate gradient method with sufficient descent property, Appl. Math. Comput., 218(14) (2012), 7421-7430.
]Search in Google Scholar
[
T. Diphofu and P. Kaelo, Another three-term conjugate gradient method close to the memoryless BFGS for large scale unconstrained optimization problems, Mediterr. J Math., 18:211 (2021).
]Search in Google Scholar
[
T. Diphofu, P. Kaelo and A. R. Tufa, A modified nonlinear conjugate gradient algorithm for unconstrained optimization and portfolio selection problems. RAIRO Oper. Res., 57(2) (2023), 817-835.
]Search in Google Scholar
[
E. D. Dolan, J. J. Moré, Benchmarking optimization software with performance profiles, Math. Program., 91 (2002), 201-214.
]Search in Google Scholar
[
M. Fang, M. Wang, M. Sun and R. Chen, A Modified Hybrid Conjugate Gradient Method for Unconstrained Optimization, J. Math., 2021(1) (2021), 1-9.
]Search in Google Scholar
[
R. Fletcher, Practical methods of optimization, Unconstrained Optimization, John Wiley & Sons, New York 1(1987).
]Search in Google Scholar
[
R. Fletcher and C. M. Reeves, Function minimization by conjugate gradients, Computer J., 7(2) (1964), 149-154.
]Search in Google Scholar
[
H. Guan and S. Wang, A Modified Conjugate Gradient Method for Solving Large-Scale Nonlinear Equations, Math. Probl. Eng., 2021:9919595 (2021), https://doi.org/10.1155/2021/9919595.
]Search in Google Scholar
[
W. W. Hager and H. Zhang, A survey of nonlinear conjugate gradient methods, Pacific J. Optim., 2 (2011), 35-58.
]Search in Google Scholar
[
M. R. Hestenes and E. Stiefel, Methods of conjugate gradients for solving linear systems, J Res. Nat. Bureau Stand., 49(6) (1952), 409-436.
]Search in Google Scholar
[
X. Jiang, J. Jian, D. Song and P. Liu, An improved Polak-Ribiére-Polyak conjugate gradient method with an efficient restart direction, Comput. Appl. Math., 40(174) (2021), 1-24.
]Search in Google Scholar
[
X. Jiang, W. Liao, J. Yin, J. Yin and J. Jian, A new family of hybrid three-term conjugate gradient methods with applications in image restoration, Numer. Algor., 91(2) (2022), 1-31.
]Search in Google Scholar
[
Y. Liu and C. Storey, Efficient generalized conjugate gradient algorithms, Part 1: Theory, J Optim. Theory Appl., 69(1) (1991), 129-137.
]Search in Google Scholar
[
H. Markowitz, Portfolio Selection, J. Finance, 7(1) (1952), 77-91.
]Search in Google Scholar
[
P. Mtagulwa and P. Kaelo, An efficient modified PRP-FR hybrid conjugate gradient method for solving unconstrained optimization problems, Appl. Numer. Math., 145 (2019), 111–120.
]Search in Google Scholar
[
A. A. Mustafa, New Spectral LS conjugate gradient method for nonlinear unconstrained optimization, Int. J Comput. Math.,100 (2023), 838–846.
]Search in Google Scholar
[
E. Polak and G. Ribiére, Note sur la convergence de directions conjugées, Rev. Francaise Informat Recherche Opèrationelle, 3e Année, 16 (1969), 35–43.
]Search in Google Scholar
[
B. T. Polyak, The conjugate gradient method in extreme problems, USSR Comput. Math. Math. Phys, 9(4) (1969), 94-112.
]Search in Google Scholar
[
I. M. Sulaiman, M. Malik, A. M. Awwal, P. Kumam, M. Mamat and S. Al-Ahmad, On three-term conjugate gradient method for optimization problems with applications on COVID-19 model and robotic motion control, Adv Cont Discr Mod., 2022:1 (2022). https://doi.org/10.1186/s13662-021-03638-9.
]Search in Google Scholar
[
Z. Wei, S. Yao and L. Liu, The convergence properties of some new conjugate gradient methods, Appl. Math. Comput., 183(2) (2006), 1341-1350.
]Search in Google Scholar
[
L. Zhang, An improved Wei-Yao-Liu nonlinear conjugate gradient method for optimization computation, Appl. Math. Comput., 215(6) (2009), 2269-2274.
]Search in Google Scholar
[
G. Zoutendijk, Nonlinear programming, computational methods, In: J. Abadie Ed., Integer and Nonlinear Programming, North-Holland, Amsterdam, 1970, pp. 37-86.
]Search in Google Scholar
