output.quadratic.90.fitness

PostsBayesian Optimization Algorithm with Decision Graphs in C++,

  0     700  30.999998  21.479855  13.099998
  1    1050  36.300003  23.652140  15.199999
  2    1400  36.300003  25.281283  14.999998
  3    1750  36.799999  27.132568  17.899998
  4    2100  37.099998  28.928282  19.599998
  5    2450  37.100002  30.519139  20.299999
  6    2800  38.100002  31.961996  23.899998
  7    3150  41.000000  33.499426  25.799997
  8    3500  41.700005  34.910284  27.799997
  9    3850  41.700005  36.289713  28.299995
 10    4200  42.500008  37.766000  30.999998
 11    4550  43.400005  38.955429  32.199997
 12    4900  43.500008  40.076859  34.299995
 13    5250  43.800003  41.020574  36.799999
 14    5600  43.900005  41.791146  37.499996
 15    5950  44.200005  42.502575  39.200001
 16    6300  44.200005  43.066433  40.699997
 17    6650  44.300003  43.454433  42.500004
 18    7000  44.400002  43.679433  42.800003
 19    7350  44.600002  43.853718  43.099998
 20    7700  44.800003  44.021432  43.299999
 21    8050  44.800003  44.177289  43.400002
 22    8400  44.800003  44.316146  43.600002
 23    8750  44.900002  44.430145  43.900005
 24    9100  45.000000  44.543860  44.000000
 25    9450  45.000000  44.651860  44.200005
 26    9800  45.000000  44.746431  44.300007
 27   10150  45.000000  44.820431  44.500000
 28   10500  45.000000  44.869288  44.599998
 29   10850  45.000000  44.923287  44.700001
 30   11200  45.000000  44.959143  44.700005
 31   11550  45.000000  45.000000  45.000000