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 )

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  1. Armand, Paul; Benoist, Joël; Orban, Dominique: Dynamic updates of the barrier parameter in primal-dual methods for nonlinear programming (2008)
  2. Benson, Hande Y.; Shanno, David F.: Interior-point methods for nonconvex nonlinear programming: Regularization and warmstarts (2008)
  3. Bhowmick, Sanjukta; Hovland, Paul D.: A polynomial-time algorithm for detecting directed axial symmetry in Hessian computational graphs (2008)
  4. Bielschowsky, Roberto H.; Gomes, Francisco A. M.: Dynamic control of infeasibility in equality constrained optimization (2008)
  5. Byrd, Richard H.; Curtis, Frank E.; Nocedal, Jorge: An inexact SQP method for equality constrained optimization (2008)
  6. Chen, Jun; Sun, Wenyu; De Sampaio, Raimundo J. B.: Numerical research on the sensitivity of nonmonotone trust region algorithms to their parameters (2008)
  7. Curtis, Frank E.; Nocedal, Jorge: Flexible penalty functions for nonlinear constrained optimization (2008)
  8. Dollar, H. S.: Constraint-style preconditioners for regularized saddle point problems (2008)
  9. Friedlander, Michael P.; Leyffer, Sven: Global and finite termination of a two-phase augmented Lagrangian filter method for general quadratic programs (2008)
  10. Gould, Nicholas I. M.: How good are projection methods for convex feasibility problems? (2008)
  11. Griffin, Joshua D.; Kolda, Tamara G.; Lewis, Robert Michael: Asynchronous parallel generating set search for linearly constrained optimization (2008)
  12. Kobayashi, Kazuhiro; Kim, Sunyoung; Kojima, Masakazu: Sparse second order cone programming formulations for convex optimization problems (2008)
  13. Liuzzi, G.; Lucidi, S.: A derivative-free algorithm for systems of nonlinear inequalities (2008)
  14. Olivares, Alberto; Moguerza, Javier M.; Prieto, Francisco J.: Nonconvex optimization using negative curvature within a modified linesearch (2008)
  15. Wild, Stefan M.; Regis, Rommel G.; Shoemaker, Christine A.: ORBIT: Optimization by radial basis function interpolation in trust-regions (2008)
  16. Armand, P.: Modification of the Wolfe line search rules to satisfy the descent condition in the Polak-Ribière-Polyak conjugate gradient method (2007)
  17. Auslender, Alfred; Silva, Paulo J. S.; Teboulle, Marc: Nonmonotone projected gradient methods based on barrier and Euclidean distances (2007)
  18. Cafieri, S.; D’apuzzo, M.; De Simone, V.; di Serafino, D.: On the iterative solution of KKT systems in potential reduction software for large-scale quadratic problems (2007)
  19. Custódio, A. L.; Vicente, L. N.: Using sampling and simplex derivatives in pattern search methods (2007)
  20. Dollar, H. S.; Gould, N. I. M.; Schilders, W. H. A.; Wathen, A. J.: Using constraint preconditioners with regularized saddle-point problems (2007)

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