# Adaptive Dynamic Disturbance Strategy for Differential Evolution Algorithm
## 4 Simulation Experiment and Algorithm Performance Analysis
### Analysis of Results
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Function** & **Algorithm** & **Optimal Value** & **Average Optimum** & **Standard Deviation** \\ \hline \multirow{4}{*}{\(f_{1}\)} & DE & \(8.10\times 10^{-6}\) & \(1.02\times 10^{-5}\) & \(2.84\times 10^{5}\) \\  & SADE & \(1.10\times 10^{-11}\) & \(3.67\times 10^{-11}\) & \(8.41\times 10^{-12}\) \\  & CAPSO & \(5.72\times 10^{-13}\) & \(1.29\times 10^{-12}\) & \(4.91\times 10^{-13}\) \\  & ADDSDE & 0 & 0 & 0 \\ \hline \multirow{4}{*}{\(f_{2}\)} & DE & \(2.57\times 10^{1}\) & \(3.59\times 10^{1}\) & \(7.96\times 10^{0}\) \\  & SADE & \(1.83\times 10^{1}\) & \(2.65\times 10^{1}\) & \(6.33\times 10^{0}\) \\  & CAPSO & \(5.42\times 10^{0}\) & \(7.56\times 10^{0}\) & \(1.41\times 10^{0}\) \\  & ADDSDE & 0 & 0 & 0 \\ \hline \multirow{4}{*}{\(f_{3}\)} & DE & \(7.94\times 10^{1}\) & \(1.19\times 10^{2}\) & \(2.91\times 10^{1}\) \\  & SADE & \(3.01\times 10^{1}\) & \(3.59\times 10^{1}\) & \(6.21\times 10^{0}\) \\  & CAPSO & \(2.10\times 10^{1}\) & \(2.53\times 10^{1}\) & \(5.31\times 10^{0}\) \\  & ADDSDE & 0 & 0 & 0 \\ \hline \multirow{4}{*}{\(f_{4}\)} & DE & \(0\) & \(3.69\times 10^{-4}\) & \(1.65\times 10^{-3}\) \\  & SADE & \(0\) & 0 & 0 \\ \cline{1-1}  & CAPSO & \(8.62\times 10^{-1}\) & \(9.52\times 10^{-1}\) & \(6.80\times 10^{-2}\) \\ \cline{1-1}  & ADSDE & 0 & 0 & 0 \\ \hline \multirow{4}{*}{\(f_{5}\)} & DE & \(1.10\times 10^{-9}\) & \(9.86\times 10^{-9}\) & \(1.37\times 10^{-8}\) \\ \cline{1-1}  & SADE & \(5.48\times 10^{-11}\) & \(6.55\times 10^{-11}\) & \(4.39\times 10^{-11}\) \\ \cline{1-1}  & CAPSO & \(3.05\times 10^{0}\) & \(3.48\times 10^{0}\) & \(2.61\times 10^{0}\) \\ \cline{1-1}  & ADDSDE & \(9.56\times 10^{-16}\) & \(9.56\times 10^{-16}\) & 0 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: 30-dimensional function optimization results. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Function** & **Algorithm** & **Optimal Value** & **Average Optimum** & **Standard Deviation** \\ \hline \multirow{4}{*}{\(f_{1}\)} & DE & \(1.20\times 10^{-4}\) & \(1.11\times 10^{-3}\) & \(1.29\times 10^{-3}\) \\  & SADE & \(1.79\times 10^{-5}\) & \(2.55\times 10^{-5}\) & \(8.47\times 10^{-6}\) \\  & CAPSO & \(4.11\times 10^{2}\) & \(6.13\times 10^{-2}\) & \(1.65\times 10^{2}\) \\  & ADDSDE & 0 & 0 & 0 \\ \hline \multirow{4}{*}{\(f_{2}\)} & DE & \(4.48\times 10^{1}\) & \(8.94\times 10^{1}\) & \(4.62\times 10^{1}\) \\  & SADE & \(4.70\times 10^{1}\) & \(6.44\times 10^{1}\) & \(1.64\times 10^{1}\) \\  & CAPSO & \(1.15\times 10^{2}\) & \(2.45\times 10^{2}\) & \(1.09\times 10^{2}\) \\  & ADDSDE & 0 & 0 & 0 \\ \hline \multirow{4}{*}{\(f_{3}\)} & DE & \(3.45\times 10^{2}\) & \(3.62\times 10^{2}\) & \(1.98\times 10^{1}\) \\  & SADE & \(1.67\times 10^{2}\) & \(1.94\times 10^{2}\) & \(1.54\times 10^{1}\) \\ \cline{1-1}  & CAPSO & \(1.16\times 10^{2}\) & \(1.63\times 10^{2}\) & \(2.98\times 10^{1}\) \\ \cline{1-1}  & ADDSDE & 0 & 0 & 0 \\ \hline \multirow{4}{*}{\(f_{4}\)} & DE & \(5.17\times 10^{-4}\) & \(3.85\times 10^{-2}\) & \(3.98\times 10^{-2}\) \\  & SADE & \(2.97\times 10^{-5}\) & \(4.53\times 10^{-5}\) & \(2.37\times 10^{-5}\) \\ \cline{1-1}  & CAPSO & \(5.92\times 10^{1}\) & \(9.83\times 10^{1}\) & \(2.52\times 10^{1}\) \\ \cline{1-1}  & ADDSDE & 0 & 0 & 0 \\ \hline \multirow{4}{*}{\(f_{5}\)} & DE & \(1.01\times 10^{-3}\) & \(1.13\times 10^{-3}\) & \(8.75\times 10^{-4}\) \\  & SADE & \(4.34\times 10^{-7}\) & \(1.02\times 10^{-6}\) & \(6.11\times 10^{-7}\) \\ \cline{1-1}  & CAPSO & \(3.76\times 10^{0}\) & \(3.98\times 10^{0}\) & \(3.71\times 10^{-1}\) \\ \cline{1-1}  & ADDSDE & \(9.56\times 10^{-16}\) & \(9.56\times 10^{-16}\) & 0 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: 50-dimensional function optimization results. Figure 1: _Cont._