CUTEst: a constrained and unconstrained testing environment with safe threads. We describe the most recent evolution of our constrained and unconstrained testing environment and its accompanying SIF decoder. Code-named SIFDecode and CUTEst , these updated versions feature dynamic memory allocation, a modern thread-safe Fortran modular design, a new Matlab interface and a revised installation procedure integrated with GALAHAD.

References in zbMATH (referenced in 60 articles , 1 standard article )

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  1. Birgin, E. G.; Martínez, J. M.: A Newton-like method with mixed factorizations and cubic regularization for unconstrained minimization (2019)
  2. Rahpeymaii, Farzad; Amini, Keyvan; Allahviranloo, Tofigh; Malkhalifeh, Mohsen Rostamy: A new class of conjugate gradient methods for unconstrained smooth optimization and absolute value equations (2019)
  3. Arreckx, Sylvain; Orban, Dominique: A regularized factorization-free method for equality-constrained optimization (2018)
  4. Audet, Charles; Conn, Andrew R.; Le Digabel, Sébastien; Peyrega, Mathilde: A progressive barrier derivative-free trust-region algorithm for constrained optimization (2018)
  5. Audet, Charles; Ihaddadene, Amina; Le Digabel, Sébastien; Tribes, Christophe: Robust optimization of noisy blackbox problems using the mesh adaptive direct search algorithm (2018)
  6. Bergou, El Houcine; Diouane, Youssef; Gratton, Serge: A line-search algorithm inspired by the adaptive cubic regularization framework and complexity analysis (2018)
  7. Birgin, E. G.; Haeser, G.; Ramos, Alberto: Augmented Lagrangians with constrained subproblems and convergence to second-order stationary points (2018)
  8. Birgin, E. G.; Martínez, J. M.: On regularization and active-set methods with complexity for constrained optimization (2018)
  9. Curtis, Frank E.; Robinson, Daniel P.; Samadi, Mohammadreza: Complexity analysis of a trust funnel algorithm for equality constrained optimization (2018)
  10. Huang, Shuai; Wan, Zhong; Zhang, Jing: An extended nonmonotone line search technique for large-scale unconstrained optimization (2018)
  11. Kuhlmann, Renke; Büskens, Christof: A primal-dual augmented Lagrangian penalty-interior-point filter line search algorithm (2018)
  12. Lenders, Felix; Kirches, C.; Potschka, A.: \texttttrlib: a vector-free implementation of the GLTR method for iterative solution of the trust region problem (2018)
  13. Li, Ming; Liu, Hongwei; Liu, Zexian: A new subspace minimization conjugate gradient method with nonmonotone line search for unconstrained optimization (2018)
  14. Liu, Jianjun; Xu, Xiangmin; Cui, Xuehui: An accelerated nonmonotone trust region method with adaptive trust region for unconstrained optimization (2018)
  15. Rees, Tyrone; Scott, Jennifer: A comparative study of null-space factorizations for sparse symmetric saddle point systems. (2018)
  16. Scott, Jennifer; Tůma, Miroslav: A Schur complement approach to preconditioning sparse linear least-squares problems with some dense rows (2018)
  17. Zhang, Hao; Ni, Qin: A new regularized quasi-Newton method for unconstrained optimization (2018)
  18. Al-Baali, Mehiddin; Caliciotti, Andrea; Fasano, Giovanni; Roma, Massimo: Exploiting damped techniques for nonlinear conjugate gradient methods (2017)
  19. Andrea, Caliciotti; Giovanni, Fasano; Massimo, Roma: Novel preconditioners based on quasi-Newton updates for nonlinear conjugate gradient methods (2017)
  20. Armand, Paul; Lankoandé, Isaï: An inexact proximal regularization method for unconstrained optimization (2017)

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