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 482 articles , 1 standard article )

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  1. Ali, M. Montaz; Oliphant, Terry-Leigh: A trajectory-based method for constrained nonlinear optimization problems (2018)
  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. Andrei, Neculai: A double parameter scaled BFGS method for unconstrained optimization (2018)
  4. Andrei, Neculai: A Dai-Liao conjugate gradient algorithm with clustering of eigenvalues (2018)
  5. Babaie-Kafaki, Saman; Ghanbari, Reza: Two adaptive Dai-Liao nonlinear conjugate gradient methods (2018)
  6. Babaie-Kafaki, Saman; Ghanbari, Reza: A linear hybridization of the Hestenes-Stiefel method and the memoryless BFGS technique (2018)
  7. Babaie-Kafaki, Saman; Rezaee, Saeed: Two accelerated nonmonotone adaptive trust region line search methods (2018)
  8. Huyer, Waltraud; Neumaier, Arnold: MINQ8: general definite and bound constrained indefinite quadratic programming (2018)
  9. Li, Dan; Zhu, Detong: An affine scaling interior trust-region method combining with line search filter technique for optimization subject to bounds on variables (2018)
  10. Li, Min: A modified Hestense-Stiefel conjugate gradient method close to the memoryless BFGS quasi-Newton method (2018)
  11. Liu, J. K.; Feng, Y. M.; Zou, L. M.: Some three-term conjugate gradient methods with the inexact line search condition (2018)
  12. 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)
  13. Öztoprak, Figen; Birbil, Ş. İlker: An alternative globalization strategy for unconstrained optimization (2018)
  14. Rezaee, Saeed; Babaie-Kafaki, Saman: A modified nonmonotone trust region line search method (2018)
  15. Yao, Shengwei; He, Donglei; Shi, Lihua: An improved Perry conjugate gradient method with adaptive parameter choice (2018)
  16. Alhawarat, Ahmad; Salleh, Zabidin: Modification of nonlinear conjugate gradient method with weak Wolfe-Powell line search (2017)
  17. Andrei, Neculai: Accelerated adaptive Perry conjugate gradient algorithms based on the self-scaling memoryless BFGS update (2017)
  18. Armand, Paul; Omheni, Riadh: A mixed logarithmic barrier-augmented Lagrangian method for nonlinear optimization (2017)
  19. Ataee Tarzanagh, D.; Nazari, P.; Reza Peyghami, M.: A nonmonotone PRP conjugate gradient method for solving square and under-determined systems of equations (2017)
  20. Babaie-Kafaki, Saman; Ghanbari, Reza: A class of adaptive dai-liao conjugate gradient methods based on the scaled memoryless BFGS update (2017)

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