CG_DESCENT

Algorithm 851: CG_DESCENT. A conjugate gradient method with guaranteed descent Recently, a new nonlinear conjugate gradient scheme was developed which satisfies the descent condition gTkdk ≤ −7/8 ‖gk‖2 and which is globally convergent whenever the line search fulfills the Wolfe conditions. This article studies the convergence behavior of the algorithm; extensive numerical tests and comparisons with other methods for large-scale unconstrained optimization are given.

This software is also peer reviewed by journal TOMS.

Keywords for this software

Anything in here will be replaced on browsers that support the canvas element

References in zbMATH (referenced in 105 articles , 1 standard article )

Showing results 1 to 20 of 105.
Sorted by year (citations)

1 2 3 4 5 6 next

  1. Abubakar, Auwal Bala; Kumam, Poom; Mohammad, Hassan; Awwal, Aliyu Muhammed: A Barzilai-Borwein gradient projection method for sparse signal and blurred image restoration (2020)
  2. Andrei, Neculai: New conjugate gradient algorithms based on self-scaling memoryless Broyden-Fletcher-Goldfarb-Shanno method (2020)
  3. Karasözen, Bülent; Uzunca, Murat; Küçükseyhan, Tuğba: Reduced order optimal control of the convective FitzHugh-Nagumo equations (2020)
  4. Li, Min: A three term Polak-Ribière-Polyak conjugate gradient method close to the memoryless BFGS quasi-Newton method (2020)
  5. Liu, Zexian; Liu, Hongwei; Dai, Yu-Hong: An improved Dai-Kou conjugate gradient algorithm for unconstrained optimization (2020)
  6. Sabi’u, Jamilu; Shah, Abdullah; Waziri, Mohammed Yusuf: Two optimal Hager-Zhang conjugate gradient methods for solving monotone nonlinear equations (2020)
  7. Tarek, Mohamed; Ray, Tapabrata: Adaptive continuation solid isotropic material with penalization for volume constrained compliance minimization (2020)
  8. Yuan, Gonglin; Wang, Xiaoliang; Sheng, Zhou: The projection technique for two open problems of unconstrained optimization problems (2020)
  9. Abubakar, Auwal Bala; Kumam, Poom: A descent Dai-Liao conjugate gradient method for nonlinear equations (2019)
  10. Abubakar, Auwal Bala; Kumam, Poom; Awwal, Aliyu Muhammed: A descent Dai-Liao projection method for convex constrained nonlinear monotone equations with applications (2019)
  11. Aminifard, Z.; Babaie-Kafaki, S.: Matrix analyses on the Dai-Liao conjugate gradient method (2019)
  12. Aminifard, Zohre; Babaie-Kafaki, Saman: An optimal parameter choice for the Dai-Liao family of conjugate gradient methods by avoiding a direction of the maximum magnification by the search direction matrix (2019)
  13. Aminifard, Zohre; Babaie-Kafaki, Saman: A modified descent Polak-Ribiére-Polyak conjugate gradient method with global convergence property for nonconvex functions (2019)
  14. Awwal, Aliyu Muhammed; Kumam, Poom; Abubakar, Auwal Bala: A modified conjugate gradient method for monotone nonlinear equations with convex constraints (2019)
  15. Babaie-Kafaki, Saman; Aminifard, Zohre: Two--parameter scaled memoryless BFGS methods with a nonmonotone choice for the initial step length (2019)
  16. Dehghani, R.; Mahdavi-Amiri, N.: Scaled nonlinear conjugate gradient methods for nonlinear least squares problems (2019)
  17. Fazzio, N. S.; Schuverdt, M. L.: Convergence analysis of a nonmonotone projected gradient method for multiobjective optimization problems (2019)
  18. Jiang, Xianzhen; Jian, Jinbao: Improved Fletcher-Reeves and Dai-Yuan conjugate gradient methods with the strong Wolfe line search (2019)
  19. Liu, Hongwei; Liu, Zexian: An efficient Barzilai-Borwein conjugate gradient method for unconstrained optimization (2019)
  20. Liu, Zexian; Liu, Hongwei: An efficient gradient method with approximately optimal stepsize based on tensor model for unconstrained optimization (2019)

1 2 3 4 5 6 next