CUTEr and SifDec: a constrained and unconstrained testing environment, revisited. The initial release of CUTE, a widely used testing environment for optimization software, was described by {it I. Bongartz}, et al. [ibid. 21, No. 1, 123--160 (1995; Zbl 0886.65058)]. A new version, now known as CUTEr, is presented. Features include reorganisation of the environment to allow simultaneous multi-platform installation, new tools for, and interfaces to, optimization packages, and a considerably simplified and entirely automated installation procedure for unix systems. The environment is fully backward compatible with its predecessor, and offers support for Fortran 90/95 and a general C/C++ Application Programming Interface. The SIF decoder, formerly a part of CUTE, has become a separate tool, easily callable by various packages. It features simple extensions to the SIF test problem format and the generation of files suited to automatic differentiation packages.

References in zbMATH (referenced in 206 articles , 1 standard article )

Showing results 21 to 40 of 206.
Sorted by year (citations)

previous 1 2 3 4 ... 9 10 11 next

  1. Zhang, Keke; Liu, Hongwei; Liu, Zexian: A new Dai-Liao conjugate gradient method with optimal parameter choice (2019)
  2. Amaioua, Nadir; Audet, Charles; Conn, Andrew R.; Le Digabel, Sébastien: Efficient solution of quadratically constrained quadratic subproblems within the mesh adaptive direct search algorithm (2018)
  3. Audet, Charles; Tribes, Christophe: Mesh-based Nelder-Mead algorithm for inequality constrained optimization (2018)
  4. Huyer, Waltraud; Neumaier, Arnold: MINQ8: general definite and bound constrained indefinite quadratic programming (2018)
  5. Nedělková, Zuzana; Lindroth, Peter; Patriksson, Michael; Strömberg, Ann-Brith: Efficient solution of many instances of a simulation-based optimization problem utilizing a partition of the decision space (2018)
  6. Öztoprak, Figen; Birbil, Ş. İlker: An alternative globalization strategy for unconstrained optimization (2018)
  7. Yao, Shengwei; He, Donglei; Shi, Lihua: An improved Perry conjugate gradient method with adaptive parameter choice (2018)
  8. Armand, Paul; Omheni, Riadh: A mixed logarithmic barrier-augmented Lagrangian method for nonlinear optimization (2017)
  9. Beiranvand, Vahid; Hare, Warren; Lucet, Yves: Best practices for comparing optimization algorithms (2017)
  10. Burdakov, Oleg; Gong, Lujin; Zikrin, Spartak; Yuan, Ya-xiang: On efficiently combining limited-memory and trust-region techniques (2017)
  11. Cano, Javier; Moguerza, Javier M.; Prieto, Francisco J.: Using improved directions of negative curvature for the solution of bound-constrained nonconvex problems (2017)
  12. Fang, Xiaowei; Ni, Qin: A frame-based conjugate gradients direct search method with radial basis function interpolation model (2017)
  13. Gao, Huan; Zhang, Hai-Bin; Li, Zhi-Bao; Tadjouddine, Emmanuel: A nonmonotone inexact Newton method for unconstrained optimization (2017)
  14. Huang, Yuanyuan; Liu, Changhe: Dai-Kou type conjugate gradient methods with a line search only using gradient (2017)
  15. Li, Xiangrong; Wang, Bopeng; Hu, Wujie: A modified nonmonotone BFGS algorithm for unconstrained optimization (2017)
  16. Morini, Benedetta; Simoncini, Valeria; Tani, Mattia: A comparison of reduced and unreduced KKT systems arising from interior point methods (2017)
  17. Sala, Ramses; Baldanzini, Niccolò; Pierini, Marco: Global optimization test problems based on random field composition (2017)
  18. Wan, Wei; Biegler, Lorenz T.: Structured regularization for barrier NLP solvers (2017)
  19. Yuan, Gonglin; Wei, Zengxin; Lu, Xiwen: Global convergence of BFGS and PRP methods under a modified weak Wolfe-Powell line search (2017)
  20. Zhou, Guanghui; Ni, Qin; Zeng, Meilan: A scaled conjugate gradient method with moving asymptotes for unconstrained optimization problems (2017)

previous 1 2 3 4 ... 9 10 11 next