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 519 articles , 1 standard article )

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  1. Facchinei, Francisco; Júdice, Joaquim; Soares, João: An active set Newton algorithm for large-scale nonlinear programs with box constraints (1998)
  2. Ford, Rupert W.; Riley, Graham D.; Freeman, Leonard T.: The development of parallel optimisation routines for th NAG parallel library (1998)
  3. Gay, David M.; Overton, Michael L.; Wright, Margaret H.: A primal-dual interior method for nonconvex nonlinear programming (1998)
  4. Kolda, Tamara G.; O’Leary, Dianne P.; Nazareth, Larry: BFGS with update skipping and varying memory (1998)
  5. Lalee, Marucha; Nocedal, Jorge; Plantenga, Todd: On the implementation of an algorithm for large-scale equality constrained optimization (1998)
  6. Lucidi, Stefano; Rochetich, Francesco; Roma, Massimo: Curvilinear stabilization techniques for truncated Newton methods in large scale unconstrained optimization (1998)
  7. Bouaricha, Ali: Algorithm 765: STENMIN: A software package for large, sparse unconstrained optimization using tensor methods (1997)
  8. Conn, A. R.; Scheinberg, K.; Toint, Ph. L.: Recent progress in unconstrained nonlinear optimization without derivatives (1997)
  9. Daydé, Michel J.; L’Excellent, Jean-Yves; Gould, Nicholas I. M.: Element-by-element preconditioners for large partially separable optimization problems (1997)
  10. Lucidi, Stefano; Roma, Massimo: Numerical experiences with new truncated Newton methods in large scale unconstrained optimization (1997)
  11. Ni, Q.; Yuan, Y.: A subspace limited memory quasi-Newton algorithm for large-scale nonlinear bound constrained optimization (1997)
  12. Shanno, David F.; Simantiraki, Evangelia M.: Interior point methods for linear and nonlinear programming (1997)
  13. Toint, Philippe L.: Non-monotone trust-region algorithms for nonlinear optimization subject to convex constraints (1997)
  14. Zhu, Ciyou; Byrd, Richard H.; Lu, Peihuang; Nocedal, Jorge: Algorithm 778: L-BFGS-B Fortran subroutines for large-scale bound-constrained optimization (1997)
  15. Breitfeld, Marc G.; Shanno, David F.: Computational experience with penalty-barrier methods for nonlinear programming (1996)
  16. Ferris, M. C.; Lucidi, S.; Roma, M.: Nonmonotone curvilinear line search methods for unconstrained optimization (1996)
  17. Bongartz, I.; Conn, A. R.; Gould, N.; Toint, Ph. L.: CUTE: Constrained and unconstrained testing environment (1995)
  18. Conn, Andrew R.; Gould, Nick; Toint, Philippe L.: Improving the decomposition of partially separable functions in the context of large-scale optimization: A first approach (1994)
  19. Jónasson, Kristján; Madsen, Kaj: Corrected sequential linear programming for sparse minimax optimization (1994)

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