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?2-[ 6]-{0.494751, 1.90302, 1.46631, 1.78217, 0.763977}
?2-[ 7]-{1.49399, 1.53351, 1.73672, 0.041168, 0.160522}
?2-[ 8]-{1.49399, -0.401642, -0.434051, -0.301575, 1.142}
?0-[ 9]-{-0.662018, 1.27142, 1.35562, 1.90302, 0.430389}
?2-[10]-{0.406036, 0.150848, 1.98966, 0.346924, -0.538483}
?3-[11]-{-0.958619, 1.142, -0.654175, 0.626953, -0.654175}
?3-[12]-{-0.978241, -0.853363, 0.037323, 0.818024, 1.92236}
?1-[13]-{-0.958619, 0.316925, 1.05463, 0.19992, 1.47864}
?3-[14]-{0.19223, 1.3107, -0.662018, 1.85046, 1.69431}
?2-[15]-{-0.321991, 1.72037, 1.46631, 0.041168, -0.42337}
?3-[16]-{0.19223, -0.42337, -0.145813, -0.022888, 0.990174}
?2-[17]-{-0.253937, 0.249176, -0.582947, -0.932801, 1.53351}
?2-[18]-{0.430389, 1.3107, -0.387329, -0.022888, 1.05463}
?2-[19]-{0.697174, -0.611939, 1.44742, 1.29065, 0.037323}
Outputs:
[ 0] = f(1.44742) = 2.44266
[ 1] = f(1.79529) = 0.73521
[ 2] = f(1.44742) = 2.44266
[ 3] = f(1.67365) = 2.23274
[ 4] = f(1.44742) = 2.44266
[ 5] = f(1.46631) = 2.27802
[ 6] = f(1.46631) = 2.27802
[ 7] = f(1.73672) = -0.587869
[ 8] = f(-0.434051) = 1.3807
[ 9] = f(-0.662018) = 1.61539
[10] = f(1.98966) = 0.36469
[11] = f(0.626953) = 1.46967
[12] = f(0.818024) = 1.43884
[13] = f(0.316925) = 0.839315
[14] = f(1.85046) = 2.85027
[15] = f(1.46631) = 2.27802
[16] = f(-0.022888) = 1.01508
[17] = f(-0.582947) = 0.702421
[18] = f(-0.387329) = 0.849855
[19] = f(1.44742) = 2.44266
As you can see, the parameter value
x
0
= 1.85046 encoded by the best of
this generation corresponds to the output
f
(
x
0
) = 2.85027 and, therefore, this
individual is a perfect solution to the problem at hand.
It is also interesting to see how close the HZero algorithm can get to the
global maximum by letting it run for a few thousands of generations until no
further improvement is observed. Consider, for instance, the evolutionary
history presented below (the generation by which these solutions were dis-
covered is shown in square brackets):
