Page 38 - IJOCTA-15-1
P. 38

S. Ben Hanachi, B. Sellami, M. Belloufi / IJOCTA, Vol.15, No.1, pp.25-34 (2025)
            Conflict of interest                               [8] Fletcher, R., & Reeves, C. M. (1964). Function
                                                                  minimization by conjugate gradients. The com-
            The authors declare no conflict of interest.          puter journal, 7(2), 149-154. https://doi.org/
                                                                  10.1093/comjnl/7.2.149
            Author contributions                               [9] Salleh, Z., & Alhawarat, A. (2016). An effi-
                                                                  cient modification of the Hestenes-Stiefel nonlin-
            Conceptualization: Badreddine Sellami                 ear conjugate gradient method with restart prop-
            Formal analysis: Sabrina Ben Hanachi                  erty. Journal of Inequalities and Applications,
            Methodology: Mohammed Belloufi                        110. https://doi.org/10.1186/s13660-016
                                                                  -1049-5
            Writing – original draft: Sabrina Ben Banachi
                                                              [10] Wei, Z., Li, G., and Qi, L. (2006). New nonlinear
            Writing – review & editing: Sabrina Ben Hanachi
                                                                  conjugate gradient formulas for large-scale uncon-
                                                                  strained optimization problems. Applied Mathe-
                                                                  matics and Computation, 179(2), 407-430. https:
            Availability of data                                  //doi.org/10.1016/j.amc.2005.11.150
                                                              [11] Yuan, G., Wei, Z., & Zhao, Q. (2014). A modi-
            The data that support the findings of this study      fied Polak–Ribi´ere–Polyak conjugate gradient al-
            are available from the corresponding author upon      gorithm for large-scale optimization problems.
            reasonable request.                                   IIE Transactions, 46(4), 397-413. https://doi.
                                                                  org/10.1080/0740817X.2012.726757
                                                              [12] Wolfe, P. (1969). Convergence conditions for as-
            References
                                                                  cent methods. Society for Industrial and Applied
             [1] Liu, J. K., & Li, S. J. New hybrid conjugate     Mathematics Review, 11(2), 226-235. https://do
                gradient method for unconstrained optimization.   i.org/10.1137/1011036
                (2014). Applied Mathematics and Computation,  [13] Wolfe, P. (1971). Convergence conditions for as-
                245, 36-43. https://doi.org/10.1016/j.amc.        cent methods. II: Some corrections. Society for In-
                2014.07.096                                       dustrial and Applied Mathematics review, 13(2),
             [2] Luo, C., Wang, L., Xie, Y., & Chen, B. (2024). A  185-188. https://doi.org/10.1137/1013035
                new conjugate gradient method for moving force  [14] Dai, Y. H., Yuan, Y. (1999). A nonlinear conju-
                identification of vehicle-bridge system. Journal of  gate gradient method with a strong global conver-
                Vibration Engineering & Technologies, 12(1), 19-  gence property. Society for Industrial and Applied
                36. https://doi.org/10.1007/s42417-022-0          Mathematics Journal on optimization, 10(1), 177-
                0824-1                                            182. https://doi.org/10.1137/S10526234973
             [3] Yuan, Y., Tsang, D. H., & Lau, V. K. (2024).     18992
                Combining Conjugate Gradient and Momentum     [15] Liu, Y., & Storey, C. (1991). Efficient generalized
                for Unconstrained Stochastic Optimization With    conjugate gradient algorithms, Part 1: Theory.
                Applications to Machine Learning. IEEE Internet   Journal of Optimization Theory and Applications,
                of Things Journal.                                69, 129-137. https://doi.org/10.1007/BF0094
             [4] Hanachi, S. B., Sellami, B., & Belloufi, M.      0464
                (2024). A new family of hybrid conjugate gradi-  [16] Ibrahim, S. M., Yakubu, U. A., & Mamat, M.
                ent method for unconstrained optimization and     (2020). Application of spectral conjugate gradi-
                its application to regression analysis. RAIRO-    ent methods for solving unconstrained optimiza-
                Operations Research. 58(1), 613-627 https://do    tion problems. An International Journal of Op-
                i.org/10.1051/ro/2023196                          timization and Control: Theories & Applications
             [5] Jiang, X., Pan, L., Liu, M., & Jian, J. (2024). A  (IJOCTA), 10(2), 198-205. https://doi.org/10
                family of spectral conjugate gradient method with  .11121/ijocta.01.2020.00859
                strong convergence and its applications in image  [17] Kaelo, P., Narayanan, S., & Thuto, M. V.
                restoration and machine learning. Journal of the  (2017). A modified quadratic hybridization of
                Franklin Institute, 107033. https://doi.org/10    Polak-Ribiere-Polyak and Fletcher-Reeves conju-
                .1016/j.jfranklin.2024.107033                     gate gradient method for unconstrained optimiza-
             [6] Balaram, B., Narayanan, M. D., & Rajendraku-     tion problems. An International Journal of Opti-
                mar, P. K. (2012). Optimal design of multi-       mization and Control: Theories & Applications
                parametric nonlinear systems using a parametric   (IJOCTA), 7(2), 177-185. https://doi.org/10
                continuation based genetic algorithm approach.    .11121/ijocta.01.2017.00339
                Nonlinear Dynamics, 67(4), 2759-2777. https:  [18] Belloufi, M., Rachid, B., & Yamina, L. (2013).
                //doi.org/10.1007/s11071-011-0187-z               Modi cation of the Armijo line search to satisfy
             [7] Hestenes, M. R., & Stiefel, E. (1952). Methods of  the convergenceproperties of HS method. An In-
                Conjugate Gradients for Solving. Journal of Re-   ternational Journal of Optimization and Control:
                search of the National Bureau of Standards, 49(1),  Theories & Applications (IJOCTA), 3(2), 145-
                409-436. https://doi.org/10.6028/jres.049         152. https://doi.org/10.11121/ijocta.01
                .044                                              .2013.00141
                                                            32
   33   34   35   36   37   38   39   40   41   42   43