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Nonlinear Conjugate Gradient Methods for Unconstrained Optimization

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  • Neculai Andrei

    (Academy of Romanian Scientists)

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Suggested Citation

  • Neculai Andrei, 2020. "Nonlinear Conjugate Gradient Methods for Unconstrained Optimization," Springer Optimization and Its Applications, Springer, number 978-3-030-42950-8, June.
    • Handle: RePEc:spr:spopap:978-3-030-42950-8
    DOI: 10.1007/978-3-030-42950-8
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    Cited by:

    1. Tiantian Zhao & Wei Hong Yang, 2023. "A Nonlinear Conjugate Gradient Method Using Inexact First-Order Information," Journal of Optimization Theory and Applications, Springer, vol. 198(2), pages 502-530, August.
    2. George Baravdish & Gabriel Eilertsen & Rym Jaroudi & B. Tomas Johansson & Lukáš Malý & Jonas Unger, 2024. "A Hybrid Sobolev Gradient Method for Learning NODEs," SN Operations Research Forum, Springer, vol. 5(4), pages 1-39, December.
    3. Abubakar, Auwal Bala & Kumam, Poom & Malik, Maulana & Ibrahim, Abdulkarim Hassan, 2022. "A hybrid conjugate gradient based approach for solving unconstrained optimization and motion control problems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 201(C), pages 640-657.
    4. Vladimir Rakočević & Milena J. Petrović, 2022. "Comparative Analysis of Accelerated Models for Solving Unconstrained Optimization Problems with Application of Khan’s Hybrid Rule," Mathematics, MDPI, vol. 10(23), pages 1-13, November.
    5. Wumei Sun & Hongwei Liu & Zexian Liu, 2021. "A Class of Accelerated Subspace Minimization Conjugate Gradient Methods," Journal of Optimization Theory and Applications, Springer, vol. 190(3), pages 811-840, September.

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