# An Improved Squirrel Search Algorithm for Global Function Optimization
## 3 The improved Squirrel Search Algorithm
### The Jumping Search Method
#### 3.2.3 Characters of the Jumping Search Method
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Name**} & \multirow{2}{*}{**D**} & \multirow{2}{*}{**Method**} & \multirow{2}{*}{**Best**} & \multirow{2}{*}{**Worst**} & \multirow{2}{*}{**Mean**} & \multirow{2}{*}{**SD**} & \multirow{2}{*}{**R**} \\ \hline \multirow{8}{*}{F20} & \multirow{8}{*}{30} & MDE & 2.0970e\(-\)07 & 0.0017 & 2.0093e\(-\)04 & 4.2588e\(-\)04 & 0 \\  & & distABC & 0.0349 & 0.9800 & 0.1546 & 0.2342 & 0 \\  & & IGSA/PSO & 0.0019 & 0.1676 & 0.0249 & 0.0340 & 0 \\  & & ADN-RSN-PSO & 1.9121e\(-\)07 & 18.8459 & 0.7225 & 3.4292 & 0 \\  & & PSO-GWO & 3.1745e\(-\)141 & 4.1132e\(-\)119 & 1.5246e\(-\)120 & 7.5032e\(-\)120 & 30 \\  & & ISSA & 1.1472e\(-\)268 & 1.7507e\(-\)232 & 6.9323e\(-\)234 & 0 & 30 \\ \cline{2-8}  & \multirow{8}{*}{50} & MDE & 4.961e\(-\)05 & 0.0076 & 0.0017 & 0.0020 & 0 \\  & & distABC & 23.2445 & 64.7154 & 36.0016 & 9.1027 & 0 \\  & & IGSA/PSO & 0.0772 & 3.2993 & 0.7989 & 0.6953 & 0 \\  & & ADN-RSN-PSO & 2.7515e\(-\)02 & 2.6995 & 1.0087 & 3.7981 & 0 \\  & & PSO-GWO & 1.1263e\(-\)143 & 1.121e\(-\)110 & 3.7456e\(-\)112 & 2.0469e\(-\)111 & 30 \\  & & ISSA & 2.4273e\(-\)279 & 3.4792e\(-\)224 & 1.1597e\(-\)225 & 0 & 30 \\ \cline{2-8}  & \multirow{8}{*}{100} & MDE & 0.0418 & 0.2153 & 0.1025 & 0.0453 & 0 \\  & & distABC & 178.0676 & 239.7760 & 209.6574 & 13.7426 & 0 \\  & & IGSA/PSO & 6.7693 & 16.2261 & 10.7582 & 2.3663 & 0 \\  & & ADN-RSN-PSO & 9.8116e\(-\)07 & 30.9275 & 2.5294 & 7.5049 & 0 \\  & & PSO-GWO & 1.7729e\(-\)144 & 5.6582e\(-\)121 & 2.2664e\(-\)122 & 1.0321e\(-\)121 & 30 \\  & & ISSA & 9.0375e\(-\)288 & 1.1851e\(-\)220 & 3.9503e\(-\)222 & 0 & 30 \\ \hline \multirow{8}{*}{F21} & \multirow{8}{*}{32} & MDE & 0.0204 & 38.6884 & 5.4340 & 10.5332 & 0 \\  & & distABC & 272.5527 & 8.4642e\(+\)04 & 1.9675e\(+\)04 & 2.1057e\(+\)04 & 0 \\  & & IGSA/PSO & 0.0468 & 20.9792 & 2.5257 & 3.8308 & 0 \\  & & ADN-RSN-PSO & 4.9194e\(-\)20 & 2.8246 & 0.1053 & 0.5147 & 9 \\  & & PSO-GWO & 1.2817e\(+\)07 & 1.2817e\(+\)07 & 1.2817e\(+\)07 & 0 & 0 \\  & & ISSA & 0 & 0 & 0 & 0 & 30 \\ \cline{2-8}  & \multirow{8}{*}{100} & MDE & 0.3480 & 360.7218 & 22.4760 & 67.4348 & 0 \\  & & distABC & 4.9677e\(+\)05 & 5.6739e\(+\)06 & 2.3595e\(+\)06 & 1.3184e\(+\)06 & 0 \\  & & IGSA/PSO & 1.2118 & 5.0887e\(+\)03 & 497.2259 & 1.0764e\(+\)03 & 0 \\  & & ADN-RSN-PSO & 3.3860e\(-\)31 & 0.0562 & 0.0020 & 0.0102 & 17 \\  & & PSO-GWO & 2.0828 e\(+\)07 & 2.0828 e\(+\)07 & 2.0828 e\(+\)07 & 0 & 0 \\  & & ISSA & 0 & 0 & 0 & 0 & 30 \\ \hline \multirow{8}{*}{F21} & \multirow{8}{*}{52} & MDE & 61.9570 & 6.2051e\(+\)03 & 1.0242e\(+\)03 & 1.3454e\(+\)03 & 0 \\  & & distABC & 3.7727e\(+\)07 & 6.2101e\(+\)07 & 5.8466e\(+\)07 & 4.7813e\(+\)06 & 0 \\ \cline{1-1}  & & IGSA/PSO & 1.0166e\(+\)04 & 6.5678e\(+\)04 & 3.5827e\(+\)04 & 1.3363e\(+\)04 & 0 \\ \cline{1-1}  & & ADN-RSN-PSO & 1.3081e\(-\)21 & 4.5014 & 0.2386 & 0.8825 & 13 \\ \cline{1-1}  & & PSO-GWO & 4.0055 e\(+\)07 & 4.0055 e\(+\)07 & 4.0055 e\(+\)07 & 0 & 0 \\ \cline{1-1} \cline{2-8}  & \multirow{8}{*}{100} & MDE & 61.9570 & 6.2051e\(+\)03 & 1.0242e\(+\)03 & 1.3454e\(+\)03 & 0 \\ \cline{1-1}  & & distABC & 3.7727e\(+\)07 & 6.2101e\(+\)07 & 5.8466e\(+\)07 & 4.7813e\(+\)06 & 0 \\ \cline{1-1}  & & IGSA/PSO & 1.0166e\(+\)04 & 6.5678e\(+\)04 & 3.5827e\(+\)04 & 1.3363e\(+\)04 & 0 \\ \cline{1-1}  & & ADN-RSN-PSO & 1.3081e\(-\)21 & 4.5014 & 0.2386 & 0.8825 & 13 \\ \cline{1-1}  & & PSO-GWO & 4.0055 e\(+\)07 & 4.0055 e\(+\)07 & 4.0055 e\(+\)07 & 0 & 0 \\ \cline{1-1} \cline{2-8}  & \multirow{8}{*}{100} & DSA & 0 & 0 & 0 & 0 & 30 \\ \cline{1-1} \cline{2-8}  & & MDE & 61.9570 & 6.2051e\(+\)03 & 1.0242e\(+\)03 & 1.3454e\(+\)03 & 0 \\ \cline{1-1}  & & distABC & 3.7727e\(+\)07 & 6.2101e\(+\)07 & 5.8466e\(+\)07 & 4.7813e\(+\)06 & 0 \\ \cline{1-1}  & & IGSA/PSO & 1.0166e\(+\)04 & 6.5678e\(+\)04 & 3.5827e\(+\)04 & 1. To further compare the performance of the six algorithms, assume that the convergence performance of ISSA is better than the other five methods.