CUTEr

CUTEr is a versatile testing environment for optimization and linear algebra solvers. The package contains a collection of test problems, along with Fortran 77, Fortran 90/95 and Matlab tools intended to help developers design, compare and improve new and existing solvers. The test problems provided are written in so-called Standard Input Format (SIF). A decoder to convert from this format into well-defined Fortran 77 and data files is available as a separate package. Once translated, these files may be manipulated to provide tools suitable for testing optimization packages. Ready-to-use interfaces to existing packages, such as MINOS, SNOPT, filterSQP, Knitro, and more, are provided. See the interfaces section for a complete list.


References in zbMATH (referenced in 460 articles , 1 standard article )

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  1. Andrei, Neculai: A double parameter scaled BFGS method for unconstrained optimization (2018)
  2. Andrei, Neculai: Accelerated adaptive Perry conjugate gradient algorithms based on the self-scaling memoryless BFGS update (2017)
  3. Armand, Paul; Omheni, Riadh: A mixed logarithmic barrier-augmented Lagrangian method for nonlinear optimization (2017)
  4. Ataee Tarzanagh, D.; Nazari, P.; Reza Peyghami, M.: A nonmonotone PRP conjugate gradient method for solving square and under-determined systems of equations (2017)
  5. Babaie-Kafaki, Saman; Ghanbari, Reza: A class of descent four-term extension of the Dai-Liao conjugate gradient method based on the scaled memoryless BFGS update (2017)
  6. Babaie-Kafaki, Saman; Ghanbari, Reza: A class of adaptive dai-liao conjugate gradient methods based on the scaled memoryless BFGS update (2017)
  7. Burdakov, Oleg; Gong, Lujin; Zikrin, Spartak; Yuan, Ya-xiang: On efficiently combining limited-memory and trust-region techniques (2017)
  8. Cano, Javier; Moguerza, Javier M.; Prieto, Francisco J.: Using improved directions of negative curvature for the solution of bound-constrained nonconvex problems (2017)
  9. Dong, Xiao Liang; Li, Wei Jun; He, Yu Bo: Some modified Yabe-Takano conjugate gradient methods with sufficient descent condition (2017)
  10. Fang, Xiaowei; Ni, Qin: A frame-based conjugate gradients direct search method with radial basis function interpolation model (2017)
  11. Gao, Huan; Zhang, Hai-Bin; Li, Zhi-Bao; Tadjouddine, Emmanuel: A nonmonotone inexact Newton method for unconstrained optimization (2017)
  12. Huang, Yuanyuan; Liu, Changhe: Dai-Kou type conjugate gradient methods with a line search only using gradient (2017)
  13. Li, Xiangrong; Wang, Bopeng; Hu, Wujie: A modified nonmonotone BFGS algorithm for unconstrained optimization (2017)
  14. Morini, Benedetta; Simoncini, Valeria; Tani, Mattia: A comparison of reduced and unreduced KKT systems arising from interior point methods (2017)
  15. Nosratipour, Hadi; Fard, Omid Solaymani; Borzabadi, Akbar Hashemi: An adaptive nonmonotone global Barzilai-Borwein gradient method for unconstrained optimization (2017)
  16. Nosratipour, Hadi; Hashemi Borzabadi, Akbar; Solaymani Fard, Omid: On the nonmonotonicity degree of nonmonotone line searches (2017)
  17. Ou, Yigui; Liu, Yuanwen: A memory gradient method based on the nonmonotone technique (2017)
  18. Sala, Ramses; Baldanzini, Niccolò; Pierini, Marco: Global optimization test problems based on random field composition (2017)
  19. Wang, Jueyu; Zhu, Detong: Derivative-free restrictively preconditioned conjugate gradient path method without line search technique for solving linear equality constrained optimization (2017)
  20. Wan, Wei; Biegler, Lorenz T.: Structured regularization for barrier NLP solvers (2017)

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