Research Article

Hybrid Genetic Grey Wolf Algorithm for Large-Scale Global Optimization

Table 6

Comparison of optimization performance of different values for HGGWA.

Function
MeanStdMeanStdMeanStdMeanStd

8.43E-605.36E-602.25E-542.03E-545.58E-534.31E-532.31E-513.16E-51
2.89E-342.31E-342.06E-331.89E-334.70E-323.65E-325.76E-304.22E-30
1.11E+001.02E+003.14E+012.19E+014.03E-012.38E-013.60E+012.16E+01
9.78E+018.36E+019.82E+017.43E+019.81E+017.34E+019.83E+014.61E+01
2.18E-031.34E-038.87E-026.67E-027.81E+006.13E+001.74E-022.34E-02
1.31E-031.13E-031.62E-032.43E-042.99E-031.04E-031.84E-031.34E-03
0.00E+000.00E+000.00E+000.00E+000.00E+000.00E+000.00E+000.00E+00
1.58E-141.23E-152.93E-141.37E-142.22E-141.49E-142.51E-141.08E-14
0.00E+000.00E+000.00E+000.00E+000.00E+000.00E+000.00E+000.00E+00
2.99E-022.49E-023.38E-021.24E-038.42E-026.14E-027.29E-028.13E-03