Solving Unconstrained Global Optimization Problems via Hybrid Swarm Intelligence Approaches
Table 4
Numerical results obtained from the proposed AIA-PSO algorithm for solving 14 UGO problems.
TP number
Function name
Global minimum
Required accuracy
Success rate (%)
MCCT (sec)
1
SHCB
−1.0316
100
−1.0316
−1.0316
−1.0316
0.00000000
39.69
2
GP
3
100
3
3
3
0.00000000
37.80
3
ES
−1
100
−1
−1
−1
0.00000000
42.08
4
B2
0
100
0.00000000
0.00000000
0.00000000
0.00000000
40.43
5
DJ
0
100
0.00000000
39.43
6
Booth
0
100
0.00000000
0.00000000
0.00000000
0.00000000
37.48
7
RC
5/
100
0.39788735
0.39788735
0.39788735
0.00000000
40.53
8
RA
−2
100
−2
−2
−2
0.00000000
39.17
9
RS2
0
100
0.00000000
37.49
10
RS5
0
100
304.23
11
SH
−186.7309
100
−186.7309
−186.7309
−186.7309
0.00000000
54.70
12
ZA2
0
100
0.00000000
0.00000000
0.00000000
0.00000000
40.31
13
ZA5
0
100
0.00000000
144.38
14
ZA10
0
100
192.06
: the objective value obtained using the best AIA-PSO solution. : mean objective value obtained using the AIA-PSO solutions. : the worst objective value obtained using the worst AIA-PSO solution.