A Novel Teaching-Learning-Based Optimization with Laplace Distribution and Experience Exchange
Table 5
Results of 10 algorithms over 30 independent times on 6 test functions of 30 dimensions with 300,000 FES.
Function
Result
PSO
DE
ABC
CS
GSO
WCA
DSA
BSA
ISA
LETLBO
F1
SD
1.05 E+02 + 1.01 E+01
1.21 E+02–2.18 E+01
2.01 E+02–1.45 E+02
3.10 E+02–4.72 E+01
3.10 E+02–5.23 E+01
2.00 E+02–1.01 E+02
7.33 E+02–1.07 E+02
6.30 E+02–2.32 E+02
7.01 E+02–2.61 E+02
1.10 E+012.11E-10
F2
SD
1.05 E+02–3.32 E+01
1.20 E+02–6.22 E+01
3.25 E+02–3.57 E+01
1.21 E+02–1.07 E+01
3.11 E+02–2.13 E+01
1.32 E+02–3.43 E+01
7.52 E+02–3.75 E+01
4.43 E+01 ≈ 2.43 E+01
1.21 E+02–2.97 E+01
6.03 E+013.24E-08
F3
SD
2.11 E+01 + 3.64E-00
1.85 E+01 + 4.21E-00
2.89 E+01–2.32e-00
2.63 E+01–1.63e-00
3.20 E+01–3.02e-00
3.00 E+01–4.63e-00
2.60 + 01–1.11 E+00
2.57 E+01 ≈ 2.52E-00
3.01 E+01–2.11e-00
2.57 E+013.39E-01
F4
SD
7.88 E+04–7.65 E+04
5.04 E+03–2.32 E+03
8.89 E+03–3.23 E+03
3.04 E+04–1.01 E+04
4.54 E+04–3.43 E+03
2.23 E+04–3.53 E+04
2.32 E+04–7.44 E+03
1.33 E+04–4.32 E+03
1.54 E+06–8.21 E+04
4.89 E+031.10 E+03
F5
SD
3.26E-00 + 2.40e-01
2.72E-00 + 3.24e-01
1.12E-00 + 9.54e-01
6.65E-00-7.61e-01
2.00E-00 + 4.43e-01
9.78E-00-2.12–00
1.76E-00 + 8.88e-01
1.69E-00 + 1.32e-00
4.36E-00-1.97e-00
3.47 e-002.93e-01
F6
SD
1.21 E+01 ≈ 6.13E-01
1.32 E+01–1.25e-01
1.31 E+01–5.92e-01
1.28 E+016.03E-01
1.30 E+015.66E-01
1.30 E+01–7.42e-01
1.30 E+01–6.06e-01
1.26 E+01–5.90e-01
1.27 E+01–5.10e-01
1.21 E+011.30E-010
-
2
4
5
6
5
6
5
3
6
+
3
2
1
0
1
0
1
2
0
≈
1
0
0
0
0
0
0
1
0
“-”, “+”, and “≈”denote that the performance of the corresponding algorithm is significantly worse than, significantly better than, and similar to that of LETLBO, respectively.
