Best normalized optimization results in fourteen benchmark functions. The values shown are the minimum objective function values found by each algorithm.
ABC
ACO
BA
CS
DE
ES
GA
HS
KH
LKH
PBIL
PSO
F01
39.13
51.65
64.63
54.80
39.31
66.38
35.21
74.39
6.59
1.00
73.39
56.78
F02
13.81
52.37
68.76
37.85
18.34
52.09
5.64
41.98
16.07
1.00
36.30
40.23
F03
13.52
6.71
91.05
37.41
14.32
53.67
5.95
121.61
1.78
1.00
84.88
46.62
F04
309.00
1.26
282.60
645.76
1.00
F05
1.00
2.70
F06
1.00
F07
2.00
4.53
6.30
4.95
3.68
6.28
3.21
4.75
1.98
1.00
5.90
4.90
F08
10.40
70.89
54.16
15.03
12.74
109.61
17.46
58.83
5.56
1.00
70.98
19.22
F09
4.60
2.18
9.10
6.98
6.28
7.80
10.10
4.83
4.53
10.01
8.14
F10
560.93
236.20
703.61
265.75
929.67
893.67
280.77
553.77
265.62
1.00
495.02
F11
20.01
32.33
75.00
44.09
29.25
83.22
31.79
88.27
23.70
1.00
86.51
54.41
F12
39.39
18.51
45.36
28.77
34.87
48.27
23.82
48.37
4.08
1.00
45.44
36.44
F13
1.00
F14
595.00
470.00
633.50
592.00
113.00
1.00
Total
0
1
0
0
0
0
1
0
0
12
0
0
values are normalized so that the minimum in each row is 1.00. These are the absolute best minima found by each algorithm.
