Simulated Annealing-Based Krill Herd Algorithm for Global Optimization
Table 1
Mean normalized optimization results in fourteen benchmark functions.
ABC
BA
CS
DE
ES
GA
HS
KH
PBIL
PSO
SA
SKH
F01
5.86
8.43
4.66
5.28
8.17
7.17
8.35
1.84
8.45
7.02
7.16
1.00
F02
5.29
28.57
4.34
7.44
20.25
7.26
17.66
6.70
17.41
15.67
1.66
1.00
F03
42.23
224.13
17.11
22.27
102.89
43.18
206.61
6.29
229.90
79.38
1.57
1.00
F04
12.54
1.00
F05
188.67
1.00
F06
1.00
F07
1.00
2.75
1.14
1.63
2.54
1.70
2.41
1.01
2.61
1.94
1.05
1.01
F08
16.46
99.06
6.23
15.71
132.91
28.27
88.88
7.30
104.89
34.65
2.75
1.00
F09
1.76
3.94
1.80
2.23
2.76
1.00
3.38
2.13
3.51
3.36
1.63
2.01
F10
416.63
970.18
101.00
514.39
586.60
441.37
537.77
267.70
555.24
387.49
71.95
1.00
F11
1.06
646.05
1.00
1.20
4.55
2.15
3.57
1.72
3.63
2.95
1.88
4.35
F12
26.50
29.62
11.15
21.16
26.82
21.31
26.94
4.23
28.03
22.22
12.75
1.00
F13
991.45
364.49
38.11
1.00
F14
225.79
87.39
116.81
794.09
233.34
28.01
459.13
3.56
1.00
Time
2.39
1.11
2.58
1.98
2.05
2.40
2.83
4.73
1.00
2.42
1.88
2.54
Total
1
0
1
0
0
1
0
0
0
0
0
11
The values are normalized so that the minimum in each row is 1.00. These are not the absolute minima found by each algorithm, but the average minima found by each algorithm.
