## 4 Proposed Algorithm
### Main Framework of the Proposed Algorithm
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & **ZS-MMBSO\_1** & \multicolumn{2}{c}{**ZS-MMBSO**} \\ \hline MMF1 & 8.38 \(\times\) 10\({}^{1}\) (2.95 \(\times\) 10\({}^{0}\)) & + & **1.99 \(\times\) 10\({}^{2}\) (1.25 \(\times\) 10\({}^{1}\))** \\ MMF2 & 3.90 \(\times\) 10\({}^{2}\) (9.44 \(\times\) 10\({}^{1}\)) & + & **1.22 \(\times\) 10\({}^{3}\) (2.21 \(\times\) 10\({}^{2}\))** \\ MMF3 & 2.94 \(\times\) 10\({}^{2}\) (7.88 \(\times\) 10\({}^{1}\)) & + & **9.28 \(\times\) 10\({}^{2}\) (1.48 \(\times\) 10\({}^{2}\))** \\ MMF4 & 8.42 \(\times\) 10\({}^{1}\) (1.25 \(\times\) 10\({}^{1}\)) & + & **3.64 \(\times\) 10\({}^{2}\) (1.10 \(\times\) 10\({}^{1}\))** \\ MMF5 & 3.36 \(\times\) 10\({}^{1}\) (2.08 \(\times\) 10\({}^{0}\)) & + & **8.24 \(\times\) 10\({}^{1}\) (5.29 \(\times\) 10\({}^{0}\))** \\ MMF6 & 3.75 \(\times\) 10\({}^{1}\) (1.65 \(\times\) 10\({}^{0}\)) & + & **8.04 \(\times\) 10\({}^{1}\) (4.25 \(\times\) 10\({}^{0}\))** \\ MMF7 & 1.39 \(\times\) 10\({}^{2}\) (6.75 \(\times\) 10\({}^{0}\)) & + & **2.86 \(\times\) 10\({}^{2}\) (1.19 \(\times\) 10\({}^{0}\))** \\ MMF8 & 2.66 \(\times\) 10\({}^{1}\) (7.53 \(\times\) 10\({}^{0}\)) & + & **1.67 \(\times\) 10\({}^{2}\) (2.03 \(\times\) 10\({}^{1}\))** \\ MMF9 & 5.30 \(\times\) 10\({}^{2}\) (1.02 \(\times\) 10\({}^{2}\)) & + & **1.53 \(\times\) 10\({}^{3}\) (5.89 \(\times\) 10\({}^{1}\))** \\ MMF10 & 2.34 \(\times\) 10\({}^{3}\) (1.53 \(\times\) 10\({}^{1}\)) & + & **3.16 \(\times\) 10\({}^{3}\) (2.97 \(\times\) 10\({}^{1}\))** \\ MMF11 & 7.98 \(\times\) 10\({}^{2}\) (6.19 \(\times\) 10\({}^{1}\)) & + & **1.15 \(\times\) 10\({}^{3}\) (4.77 \(\times\) 10\({}^{1}\))** \\ MMF12 & 1.33 \(\times\) 10\({}^{3}\) (2.23 \(\times\) 10\({}^{1}\)) & + & **1.83 \(\times\) 10\({}^{3}\) (6.82 \(\times\) 10\({}^{1}\))** \\ MMF13 & 4.36 \(\times\) 10\({}^{1}\) (9.91 \(\times\) 10\({}^{0}\)) & + & **7.76 \(\times\) 10\({}^{1}\) (3.84 \(\times\) 10\({}^{0}\))** \\ MMF14 & 2.68 \(\times\) 10\({}^{1}\) (1.92 \(\times\) 10\({}^{0}\)) & + & **5.77 \(\times\) 10\({}^{1}\)** (8.39 \(\times\) 10\({}^{-1}\))** \\ MMF15 & 3.90 \(\times\) 10\({}^{1}\) (1.20 \(\times\) 10\({}^{0}\)) & + & **7.76 \(\times\) 10\({}^{1}\) (1.27 \(\times\) 10\({}^{0}\))** \\ MMF1\_z & 9.62 \(\times\) 10\({}^{1}\) (5.76 \(\times\) 10\({}^{0}\)) & + & **2.70 \(\times\) 10\({}^{2}\) (1.90 \(\times\) 10\({}^{1}\))** \\ MMF1\_e & 5.37 \(\times\) 10\({}^{0}\) (1.59 \(\times\) 10\({}^{0}\)) & + & **8.23 \(\times\) 10\({}^{0}\)** (6.20 \(\times\) 10\({}^{-1}\))** \\ MMF14\_a & 2.18 \(\times\) 10\({}^{1}\) (1.23 \(\times\) 10\({}^{0}\)) & + & **4.94 \(\times\) 10\({}^{1}\)** (9.01 \(\times\) 10\({}^{-1}\))** \\ MMF15\_a & 3.07 \(\times\) 10\({}^{1}\) (1.96 \(\times\) 10\({}^{0}\)) & + & **6.80 \(\times\) 10\({}^{1}\)** (1.40 \(\times\) 10\({}^{0}\))** \\ SYM\_PART simple & 3.70 \(\times\) 10\({}^{1}\) (1.25 \(\times\) 10\({}^{1}\)) & + & **9.22 \(\times\) 10\({}^{1}\)** (9.45 \(\times\) 10\({}^{0}\))** \\ SYM\_PART rotated & 6.30 \(\times\) 10\({}^{1}\) (8.06 \(\times\) 10\({}^{0}\)) & + & **1.25 \(\times\) 10\({}^{2}\)** (1.45 \(\times\) 10\({}^{1}\))** \\ Omni\_test & 1.98 \(\times\) 10\({}^{0}\) (5.10 \(\times\) 10\({}^{-1}\)) & + & **3.04 \(\times\) 10\({}^{1}\)** (4.22 \(\times\) 10\({}^{0}\))** \\ \hline \hline \end{tabular}
\begin{tabular}{c c} + & 22 \\ - & 0 \\ - & 0 \\ \end{tabular}
\end{table} 
Table 3: Mean and standard deviation values of _PSP_ obtained by ZS-MMBSO and ZS-MMBSO_1. strategy. It is because the novel individual generation strategy can balance the global exploration and local exploitation. The Gaussian mutation used in the early stage can explore the entire search space and find the potential regions where the optimal solution may be located. By using the information of the non-dominated solutions, the DE/current-to-best/1 can guide individuals to search the potential regions and locate more equivalent solutions. The mutation strategy used in the latter stage has a good exploitation ability and can speed up the population convergence.