A Novel Hybrid Bat Algorithm with Harmony Search for Global Numerical Optimization
Table 4
Best normalized optimization results in fourteen benchmark functions. The values shown are the minimum objective function values found by each algorithm.
ā
ACO
BA
BBO
DE
ES
GA
HS
HSBA
PSO
SGA
F01
1.85
2.31
1.00
1.43
2.25
2.03
2.30
1.05
1.91
1.04
F02
10.42
14.48
1.09
4.22
10.39
4.03
9.91
1.00
8.28
1.33
F03
2.73
46.22
1.87
4.47
21.38
8.02
43.24
1.00
16.75
1.76
F04
4.4E6
5.0E6
1.2E3
1.9E4
2.2E6
3.0E4
4.2E6
1.00
3.755
3.22
F05
3.0E4
3.2E4
51.01
386.33
1.6E4
884.46
2.6E4
1.00
4.113
4.57
F06
58.51
992.55
6.50
24.69
808.48
59.24
746.91
1.00
189.71
2.02
F07
5.71
8.53
1.25
5.13
7.94
5.23
7.47
1.00
6.00
1.68
F08
26.42
25.03
1.48
3.70
33.52
6.16
21.50
1.00
7.75
1.45
F09
2.43
8.66
1.28
4.90
5.93
2.09
7.28
1.00
7.40
1.42
F10
1.89
4.94
1.18
2.66
3.00
2.08
2.76
1.00
2.01
1.74
F11
7.74
12.61
1.21
3.36
12.14
6.01
9.60
1.00
7.81
1.62
F12
1.33
2.33
1.44
1.69
2.08
1.74
2.11
1.00
1.70
1.21
F13
28.04
56.57
2.17
5.54
60.57
19.71
52.86
1.00
20.98
2.28
F14
4.28
54.02
1.97
4.85
33.61
10.60
49.11
1.00
19.72
1.85
*The values are normalized so that the minimum in each row is 1.00. These are the absolute best minima found by each algorithm.