Software for Derivative-free Unconstrained Nonlinear Optimization WEDGE is designed for solving problems in which the objective function is smooth and the number of variables is moderate, but derivativesare not available. The method generates a model that interpolates the objective function at a set of sample points, and uses trust regions to promote convergence. A geometric constraint (or wedge) aims at keeping the sample points non-degenerate at each iteration. The code has been developed at the Optimization Center, a joint venture of Argonne National Laboratory and Northwestern University.

References in zbMATH (referenced in 30 articles , 1 standard article )

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  1. Arouxét, Ma.Belén; Echebest, Nélida E.; Pilotta, Elvio A.: Inexact restoration method for nonlinear optimization without derivatives (2015)
  2. Yuan, Ya-xiang: Recent advances in trust region algorithms (2015)
  3. Zhang, Zaikun: Sobolev seminorm of quadratic functions with applications to derivative-free optimization (2014)
  4. Zhang, Hongchao; Conn, Andrew R.: On the local convergence of a derivative-free algorithm for least-squares minimization (2012)
  5. Arouxét, Ma.Belén; Echebest, Nélida; Pilotta, Elvio A.: Active-set strategy in Powell’s method for optimization without derivatives (2011)
  6. Gratton, Serge; Toint, Philippe L.; Tröltzsch, Anke: An active-set trust-region method for derivative-free nonlinear bound-constrained optimization (2011)
  7. Wild, Stefan M.; Shoemaker, Christine: Global convergence of radial basis function trust region derivative-free algorithms (2011)
  8. Scheinberg, K.; Toint, Ph.L.: Self-correcting geometry in model-based algorithms for derivative-free unconstrained optimization (2010)
  9. Conn, Andrew R.; Scheinberg, Katya; Vicente, Luís N.: Global convergence of general derivative-free trust-region algorithms to first- and second-order critical points (2009)
  10. Deng, Geng; Ferris, Michael C.: Variable-number sample-path optimization (2009)
  11. Fasano, Giovanni; Morales, José Luis; Nocedal, Jorge: On the geometry phase in model-based algorithms for derivative-free optimization (2009)
  12. Shi, Zhen-Jun; Xu, Zhiwei: The convergence of subspace trust region methods (2009)
  13. Conn, Andrew R.; Scheinberg, Katya; Vicente, Luís N.: Geometry of sample sets in derivative-free optimization: Polynomial regression and underdetermined interpolation (2008)
  14. Conn, A.R.; Scheinberg, K.; Vicente, Luís N.: Geometry of interpolation sets in derivative free optimization (2008)
  15. Karasözen, Bülent: Survey of trust-region derivative free optimization methods (2007)
  16. Regis, Rommel G.; Shoemaker, Christine A.: Parallel radial basis function methods for the global optimization of expensive functions (2007)
  17. Regis, Rommel G.; Shoemaker, Christine A.: Improved strategies for radial basis function methods for global optimization (2007)
  18. Wang, Xiaogang; Liang, Dong; Feng, Xingdong; Ye, Lu: A derivative-free optimization algorithm based on conditional moments (2007)
  19. Apkarian, Pierre; Noll, Dominikus: Controller design via nonsmooth multidirectional search (2006)
  20. Driessen, Lonneke; Brekelmans, Ruud; Hamers, Herbert; den Hertog, Dick: On $D$-optimality based trust regions for black-box optimization problems (2006)

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