# A Novel Dynamic Generalized Opposition-Based Grey Wolf Optimization Algorithm
## 4 Experiments and Discussion
### Simulation Experiments

Table 3: _Cont._ \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Function** & **Algorithm** & **Best** & **Worst** & **Mean** & **Std.** \\ \hline \multirow{8}{*}{F13} & BA & 1.992 & 22.90 & 11.13 & 6.28 \\  & ABC & 0.998 & 0.998 & 0.998 & \(5.14\times 10^{-6}\) \\  & PSO & 0.998 & 3.968 & 1.92 & 1.10 \\  & MFO & 0.998 & 5.93 & 1.59 & 1.18 \\  & ALO & 0.998 & 1.99 & 1.16 & 0.38 \\  & GWO & 0.998 & 12.67 & 3.73 & 4.33 \\  & DOGWO & **0.998** & 2.98 & 1.19 & 0.60 \\ \hline \multirow{8}{*}{F14} & BA & \(3.07\times 10^{-4}\) & 0.10 & \(1.37\times 10^{-2}\) & \(1.91\times 10^{-2}\) \\  & ABC & \(9.39\times 10^{-4}\) & \(1.20\times 10^{-3}\) & \(1.10\times 10^{-3}\) & \(6.98\times 10^{-5}\) \\  & PSO & \(8.69\times 10^{-4}\) & \(1.90\times 10^{-3}\) & \(1.00\times 10^{-3}\) & \(1.70\times 10^{-4}\) \\  & MFO & \(3.09\times 10^{-4}\) & \(1.66\times 10^{-3}\) & \(9.66\times 10^{-4}\) & \(4.04\times 10^{-4}\) \\  & ALO & \(3.08\times 10^{-4}\) & \(2.04\times 10^{-2}\) & \(3.33\times 10^{-3}\) & \(6.78\times 10^{-3}\) \\  & GWO & \(3.07\times 10^{-4}\) & \(2.04\times 10^{-2}\) & \(2.30\times 10^{-3}\) & \(6.10\times 10^{-3}\) \\  & DOGWO & \(3.07\times 10^{-4}\) & \(3.07\times 10^{-4}\) & \(3.07\times 10^{-4}\) & \(7.54\times 10^{-9}\) \\ \hline \multirow{8}{*}{F15} & BA & \(-1.0316\) & \(-1.0316\) & \(-1.0316\) & \(1.44\times 10^{-5}\) \\  & ABC & \(-1.0316\) & \(-1.0316\) & \(-1.0316\) & \(1.25\times 10^{-6}\) \\  & PSO & \(-1.0316\) & \(-1.0315\) & \(-1.0316\) & \(3.37\times 10^{-5}\) \\  & MFO & \(-1.0316\) & \(-1.0316\) & \(-1.0316\) & \(6.78\times 10^{-16}\) \\  & ALO & \(-1.0316\) & \(-1.0316\) & \(-1.0316\) & \(5.19\times 10^{-14}\) \\  & GWO & \(-1.0316\) & \(-1.0316\) & \(-1.0316\) & \(7.42\times 10^{-6}\) \\  & DOGWO & \(-1.0316\) & \(-1.0316\) & \(-1.0316\) & \(3.34\times 10^{-9}\) \\ \hline \multirow{8}{*}{F16} & BA & 0.3979 & 0.3979 & 0.3979 & \(3.64\times 10^{-5}\) \\  & ABC & 0.3979 & 0.3979 & 0.3979 & \(8.37\times 10^{-8}\) \\  & PSO & 0.3979 & 0.4136 & 0.3996 & \(2.90\times 10^{-3}\) \\  & MFO & 0.3979 & 0.3979 & 0.3979 & 0 \\  & ALO & 0.3979 & 0.3979 & 0.3979 & \(3.05\times 10^{-14}\) \\  & GWO & 0.3979 & 0.3979 & 0.3979 & \(3.65\times 10^{-7}\) \\  & DOGWO & **0.3979** & **0.3979** & **0.3979** & \(4.36\times 10^{-8}\) \\ \hline \multirow{8}{*}{F17} & BA & 3 & 3 & 3 & \(1.18\times 10^{-8}\) \\  & ABC & 3 & 3 & 3 & \(8.24\times 10^{-11}\) \\  & PSO & 3 & 3.0003 & 3 & \(7.22\times 10^{-5}\) \\  & MFO & 3 & 3 & \(2.68\times 10^{-13}\) \\  & ALO & 3 & 3 & 3 & \(1.41\times 10^{-15}\) \\  & GWO & 3 & 3 & 3 & \(3.61\times 10^{-6}\) \\  & DOGWO & **3** & **3** & **3** & \(1.41\times 10^{-7}\) \\ \hline \multirow{8}{*}{F18} & BA & \(-1\) & 0 & \(-0.2333\) & 0.4302 \\  & ABC & \(-1\) & \(-1\) & \(-1\) & \(1.21\times 10^{-10}\) \\  & PSO & \(-1\) & \(-0.9982\) & \(-0.9995\) & \(4.71\times 10^{-4}\) \\  & MFO & \(-1\) & \(-1\) & \(-1\) & 0 \\  & ALO & \(-1\) & \(-1\) & \(-1\) & \(7.11\times 10^{-12}\) \\  & GWO & \(-1\) & \(-1\) & \(-1\) & \(1.23\times 10^{-7}\) \\  & DOGWO & **\(-1\)** & \(-1\)** & \(-1\) & \(1.49\times 10^{-7}\) \\ \hline \multirow{8}{*}{F19} & BA & \(-3.86\) & \(-3.86\) & \(-3.86\) & \(1.65\times 10^{-8}\) \\  & ABC & \(-3.86\) & \(-3.86\) & \(-3.86\) & \(1.33\times 10^{-15}\) \\  & PSO & \(-3.86\) & \(-3.82\) & \(-3.85\) & \(9.70\times 10^{-3}\) \\ \cline{1-1}  & MFO & \(-3.86\) & \(-3.86\) & \(-3.86\) & \(2.71\times 10^{-15}\) \\ \cline{1-1}  & ALO & \(-3.86\) & \(-3.86\) & \(-3.86\) & \(1.08\times 10^{-14}\) \\ \cline{1-1}  & GWO & \(-3.86\) & \(-3.86\) & \(-3.86\) & \(2.75\times 10^{-3}\) \\ \cline{1-1}  & DOGWO & **\(-3.86\)** & \(-3.86\) & \(-3.86\) & \(2.97\times 10^{-3}\) \\ \hline \end{tabular}
\end{table} 
Table 3: _Cont._