SifDec

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. Fasano, Giovanni; Roma, Massimo: Iterative computation of negative curvature directions in large scale optimization (2007)
  2. Lewis, Robert Michael; Shepherd, Anne; Torczon, Virginia: Implementing generating set search methods for linearly constrained minimization (2007)
  3. Moguerza, Javier M.; Olivares, Alberto; Prieto, Francisco J.: A note on the use of vector barrier parameters for interior-point methods (2007)
  4. Rees, Tim; Greif, Chen: A preconditioner for linear systems arising from interior point optimization methods (2007)
  5. Sainvitu, Caroline; Toint, Philippe L.: A filter-trust-region method for simple-bound constrained optimization (2007)
  6. Audet, Charles; Orban, Dominique: Finding optimal algorithmic parameters using derivative-free optimization (2006)
  7. Dollar, H. Sue; Gould, Nicholas I. M.; Schilders, Wil H. A.; Wathen, Andrew J.: Implicit-factorization preconditioning and iterative solvers for regularized saddle-point systems (2006)
  8. Golub, Gene H.; Greif, Chen; Varah, James M.: An algebraic analysis of a block diagonal preconditioner for saddle point systems (2006)
  9. Greif, Chen; Varah, James M.: Minimizing the condition number for small rank modifications (2006)
  10. Oberlin, Christina; Wright, Stephen J.: Active set identification in nonlinear programming (2006)
  11. Sun, Wenyu; Yuan, Yaxiang: Optimization theory and methods. Nonlinear programming (2006)
  12. Wächter, Andreas; Biegler, Lorenz T.: On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming (2006)
  13. Waltz, R. A.; Morales, J. L.; Nocedal, J.; Orban, D.: An interior algorithm for nonlinear optimization that combines line search and trust region steps (2006)
  14. Wang, Zhou-Hong; Yuan, Ya-Xiang: A subspace implementation of quasi-Newton trust region methods for unconstrained optimization (2006)
  15. Zhou, Bin; Gao, Li; Dai, Yuhong: Monotone projected gradient methods for large-scale box-constrained quadratic programming (2006)
  16. Colson, Benoît; Toint, Philippe L.: Optimizing partially separable functions without derivatives (2005)
  17. Duff, Iain S.; Pralet, Stéphane: Strategies for scaling and pivoting for sparse symmetric indefinite problems (2005)
  18. Friedlander, Michael P.; Saunders, Michael A.: A globally convergent linearly constrained Lagrangian method for nonlinear optimization (2005)
  19. Gill, Philip E.; Murray, Walter; Saunders, Michael A.: SNOPT: an SQP algorithm for large-scale constrained optimization (2005)
  20. Vanden Berghen, Frank; Bersini, Hugues: CONDOR, a new parallel, constrained extension of Powell’s UOBYQA algorithm: Experimental results and comparison with the DFO algorithm (2005)

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