## 3 Numerical Experiments and Analysis
### Hybrid Algorithm Based on CC-SHADE-ML and MTS-LS1
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline  & \(\mathbf{F_{1}}\) & \(\mathbf{F_{2}}\) & \(\mathbf{F_{3}}\) & \(\mathbf{F_{4}}\) & \(\mathbf{F_{5}}\) & \(\mathbf{F_{6}}\) & \(\mathbf{F_{7}}\) & \(\mathbf{F_{8}}\) \\ \hline \multirow{8}{*}{\(1.2\times 10^{5}\)} & BEST & \(3.91\times 10^{3}\) & \(5.94\times 10^{3}\) & \(2.11\times 10^{1}\) & \(6.35\times 10^{10}\) & \(4.58\times 10^{6}\) & \(1.05\times 10^{6}\) & \(7.05\times 10^{8}\) & \(9.88\times 10^{14}\) \\  & MEADIAN & \(5.49\times 10^{3}\) & \(8.47\times 10^{3}\) & \(2.12\times 10^{1}\) & \(1.92\times 10^{11}\) & \(6.12\times 10^{6}\) & \(1.06\times 10^{6}\) & \(2.74\times 10^{9}\) & \(2.49\times 10^{15}\) \\  & WORST & \(7.60\times 10^{3}\) & \(9.44\times 10^{3}\) & \(2.13\times 10^{1}\) & \(4.74\times 10^{11}\) & \(7.28\times 10^{6}\) & \(1.06\times 10^{6}\) & \(4.78\times 10^{9}\) & \(3.05\times 10^{16}\) \\  & MEAN & \(5.63\times 10^{3}\) & \(7.99\times 10^{3}\) & \(2.12\times 10^{1}\) & \(2.00\times 10^{11}\) & \(6.12\times 10^{6}\) & \(1.06\times 10^{6}\) & \(2.52\times 10^{9}\) & \(6.75\times 10^{15}\) \\  & STD & \(1.34\times 10^{3}\) & \(1.41\times 10^{3}\) & \(7.55\times 10^{2}\) & \(1.32\times 10^{11}\) & \(1.04\times 10^{6}\) & \(3.06\times 10^{3}\) & \(1.31\times 10^{9}\) & \(1.06\times 10^{6}\) \\ \hline \multirow{8}{*}{\(6.0\times 10^{5}\)} & BEST & \(0.00\times 10^{9}\) & \(1.04\times 10^{3}\) & \(2.00\times 10^{1}\) & \(8.86\times 10^{9}\) & \(1.66\times 10^{6}\) & \(1.04\times 10^{6}\) & \(1.81\times 10^{7}\) & \(7.66\times 10^{13}\) \\  & MEADIAN & \(0.00\times 10^{9}\) & \(1.18\times 10^{3}\) & \(2.00\times 10^{1}\) & \(3.92\times 10^{10}\) & \(3.87\times 10^{6}\) & \(1.05\times 10^{6}\) & \(1.97\times 10^{8}\) & \(3.56\times 10^{14}\) \\  & WORST & \(1.54\times 10^{32}\) & \(1.49\times 10^{3}\) & \(2.00\times 10^{1}\) & \(9.74\times 10^{10}\) & \(5.59\times 10^{6}\) & \(1.05\times 10^{6}\) & \(6.84\times 10^{8}\) & \(2.14\times 10^{15}\) \\  & MEAN & \(3.07\times 10^{33}\) & \(1.18\times 10^{3}\) & \(2.00\times 10^{1}\) & \(4.85\times 10^{10}\) & \(3.61\times 10^{6}\) & \(1.05\times 10^{6}\) & \(2.33\times 10^{8}\) & \(5.32\times 10^{14}\) \\  & STD & \(6.87\times 10^{33}\) & \(1.61\times 10^{2}\) & \(1.41\times 10^{5}\) & \(3.21\times 10^{10}\) & \(1.58\times 10^{6}\) & \(3.16\times 10^{3}\) & \(2.54\times 10^{8}\) & \(7.21\times 10^{14}\) \\ \hline \multirow{8}{*}{\(3.0\times 10^{6}\)} & BEST & \(0.00\times 10^{9}\) & \(7.42\times 10^{2}\) & \(2.00\times 10^{1}\) & \(2.80\times 10^{9}\) & \(1.61\times 10^{6}\) & \(1.03\times 10^{6}\) & \(1.81\times 10^{5}\) & \(3.77\times 10^{13}\) \\  & MEADIAN & \(0.00\times 10^{9}\) & \(7.77\times 10^{2}\) & \(2.00\times 10^{1}\) & \(3.11\times 10^{9}\) & \(3.87\times 10^{6}\) & \(1.04\times 10^{6}\) & \(5.17\times 10^{5}\) & \(6.87\times 10^{13}\) \\  & WORST & \(0.00\times 10^{9}\) & \(1.33\times 10^{3}\) & \(2.00\times 10^{1}\) & \(9.54\times 10^{9}\) & \(5.05\times 10^{6}\) & \(1.05\times 10^{6}\) & \(7.00\times 10^{5}\) & \(1.11\times 10^{14}\) \\  & MEAN & \(0.00\times 10^{9}\) & \(8.66\times 10^{2}\) & \(2.00\times 10^{1}\) & \(4.26\times 10^{9}\) & \(3.28\times 10^{6}\) & \(1.04\times 10^{6}\) & \(4.50\times 10^{5}\) & \(6.90\times 10^{13}\) \\  & STD & \(0.00\times 10^{9}\) & \(2.07\times 10^{2}\) & \(1.41\times 10^{5}\) & \(2.47\times 10^{9}\) & \(1.28\times 10^{6}\) & \(