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higlighted_results_ill-conditioned_functions [2011/11/03 11:40]
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higlighted_results_ill-conditioned_functions [2011/11/03 14:17] (current)
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-Empirical runtime distributions on ill-conditioned functions (f10-f14) with target values in {100, ..., 1e-8} in dimension 20.+Empirical runtime distributions on //ill-conditioned// functions (f10: High conditioning Ellipsoid, f11: Discus, f12: Bent Cigar, f13: Sharp Ridge, f14: Different Powers) with target values in {100, ..., 1e-8} in dimension 20.
  
-The following algorithms perform particularly well up to their individual maximum number of function evaluations: GLOBAL, iAMALGAM and BIPOP-CMA-ES.+The following algorithms perform particularly well up to their individual maximum number of function evaluations: //GLOBAL// (Samplingclustering and local search using BFGS or Nelder-Mead), //iAMALGAM// (Adapted Maximum-Likelihood Gaussian Model Iterated Density Estimation Algorithm with no-improvement stretch, anticipated mean shift and interlaced restarts with one large or several small populations  with incremental model building) and //BIPOP-CMA-ES// (CMA-ES restarted with budgets for small and large population size).
higlighted_results_ill-conditioned_functions.txt · Last modified: 2011/11/03 14:17 by vhm
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