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.

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References in zbMATH (referenced in 124 articles , 1 standard article )

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  1. Awwal, A. M.; Kumam, Poom; Mohammad, Hassan; Watthayu, Wiboonsak; Abubakar, A. B.: A Perry-type derivative-free algorithm for solving nonlinear system of equations and minimizing (\ell_1) regularized problem (2021)
  2. Ivanov, Branislav; Stanimirović, Predrag S.; Shaini, Bilall I.; Ahmad, Hijaz; Wang, Miao-Kun: A novel value for the parameter in the Dai-Liao-type conjugate gradient method (2021)
  3. Sutti, Marco; Vandereycken, Bart: Riemannian multigrid line search for low-rank problems (2021)
  4. Abubakar, Auwal Bala; Kumam, Poom; Mohammad, Hassan; Awwal, Aliyu Muhammed: A Barzilai-Borwein gradient projection method for sparse signal and blurred image restoration (2020)
  5. Andrei, Neculai: New conjugate gradient algorithms based on self-scaling memoryless Broyden-Fletcher-Goldfarb-Shanno method (2020)
  6. Cao, Junyue; Wu, Jinzhao: A descent conjugate gradient algorithm for optimization problems and its applications in image restoration and compression sensing (2020)
  7. Cao, Junyue; Wu, Jinzhao: A conjugate gradient algorithm and its applications in image restoration (2020)
  8. Karasözen, Bülent; Uzunca, Murat; Küçükseyhan, Tuğba: Reduced order optimal control of the convective FitzHugh-Nagumo equations (2020)
  9. Li, Min: A three term Polak-Ribière-Polyak conjugate gradient method close to the memoryless BFGS quasi-Newton method (2020)
  10. Liu, Zexian; Liu, Hongwei; Dai, Yu-Hong: An improved Dai-Kou conjugate gradient algorithm for unconstrained optimization (2020)
  11. Sabi’u, Jamilu; Shah, Abdullah; Waziri, Mohammed Yusuf: Two optimal Hager-Zhang conjugate gradient methods for solving monotone nonlinear equations (2020)
  12. Stanimirović, Predrag S.; Ivanov, Branislav; Ma, Haifeng; Mosić, Dijana: A survey of gradient methods for solving nonlinear optimization (2020)
  13. Tarek, Mohamed; Ray, Tapabrata: Adaptive continuation solid isotropic material with penalization for volume constrained compliance minimization (2020)
  14. Yuan, Gonglin; Wang, Xiaoliang; Sheng, Zhou: Family weak conjugate gradient algorithms and their convergence analysis for nonconvex functions (2020)
  15. Yuan, Gonglin; Wang, Xiaoliang; Sheng, Zhou: The projection technique for two open problems of unconstrained optimization problems (2020)
  16. Abubakar, Auwal Bala; Kumam, Poom: A descent Dai-Liao conjugate gradient method for nonlinear equations (2019)
  17. Abubakar, Auwal Bala; Kumam, Poom; Awwal, Aliyu Muhammed: A descent Dai-Liao projection method for convex constrained nonlinear monotone equations with applications (2019)
  18. Aminifard, Z.; Babaie-Kafaki, S.: Matrix analyses on the Dai-Liao conjugate gradient method (2019)
  19. Aminifard, Zohre; Babaie-Kafaki, Saman: A modified descent Polak-Ribiére-Polyak conjugate gradient method with global convergence property for nonconvex functions (2019)
  20. 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)

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