@@ -42,6 +42,16 @@ result = bboptimize(penalized_points15; SearchRange = (0.0, 1.0), NumDimensions
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MaxTime = MaxMinutes * 60 , Method = :dxnes )
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best_dxnes = best_candidate (result)
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+ # Run the default (Adaptive DE) method for same amount of time on penalized function
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+ result = bboptimize (penalized_points15; SearchRange = (0.0 , 1.0 ), NumDimensions = Dims,
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+ MaxTime = MaxMinutes * 60 )
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+ best_de_pen = best_candidate (result)
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+
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+ # But DE need no penalization since it respects search range bounds:
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+ result = bboptimize (points15; SearchRange = (0.0 , 1.0 ), NumDimensions = Dims,
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+ MaxTime = MaxMinutes * 60 )
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+ best_de = best_candidate (result)
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+
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# Run several methods several times:
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BlackBoxOptim. repeated_bboptimize (2 , prob, Dims, [
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:generating_set_search ,
@@ -52,3 +62,5 @@ BlackBoxOptim.repeated_bboptimize(2, prob, Dims, [
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println (" xNES points15 fitness = " , points15 (best_xnes))
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println (" dxNES points15 fitness = " , points15 (best_dxnes))
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+ println (" Adaptive DE (default, penalized) points15 fitness = " , points15 (best_de_pen))
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+ println (" Adaptive DE (default) points15 fitness = " , points15 (best_de))
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