# A Novel Hybrid Harris Hawk-Arithmetic Optimization Algorithm for Industrial Wireless Mesh Networks
## 4 Results and Discussion
### Performance Analysis on Benchmark Functions
#### 4.1.3 Quantitative Analysis
Dev & 0.0201 & \(10.3480\) & \(1.23\times 10^{1}\) & \(2.37\times 10^{-8}\) & \(25.8984\) & \(1.25\times 10^{-50}\) & \(8.83\times 10^{-8}\) \\ \hline \multirow{4}{*}{F5} & \multirow{4}{*}{0} & Mean & 28.2947 & \(1.36\times 10^{4}\) & \(3.17\times 10^{4}\) & \(26.985\) & \(27.3725\) & \(0.0067\) & \(5.22\times 10^{-4}\) \\  & & Best & \(26.9909\) & \(133.2200\) & \(38.2476\) & \(25.2216\) & \(26.6853\) & \(1.47\times 10^{-5}\) & \(3.08\times 10^{-12}\) \\  & & Worst & \(28.9331\) & \(9.04\times 10^{4}\) & \(6.42\times 10^{5}\) & \(28.5425\) & \(28.7346\) & \(0.0465\) & \(0.0088\) \\  & & Std. Dev & 0.4033 & \(3.12\times 10^{4}\) & \(1.12\times 10^{5}\) & \(0.7227\) & \(0.4473\) & \(0.0086\) & \(0.0018\) \\ \hline \multirow{4}{*}{F6} & \multirow{4}{*}{0} & Mean & 2.8830 & \(797.8558\) & \(9.8129\) & \(0.4537\) & \(0.0811\) & \(4.67\times 10^{-5}\) & \(1.78\times 10^{-6}\) \\  & & Best & \(2.2110\) & \(0.2982\) & \(4.0532\) & \(3.75\times 10^{-5}\) & \(0.0124\) & \(8.73\times 10^{-8}\) & \(1.65\times 10^{-10}\) \\  & & Worst & \(3.5479\) & \(1.01\times 10^{4}\) & \(61.0512\) & \(1.2572\) & \(0.3644\) & \(3.50\times 10^{-4}\) & \(3.41\times 10^{-5}\) \\  & & Std. Dev & 0.2956 & \(2.73\times 10^{3}\) & \(10.1503\) & \(0.3654\) & \(0.0844\) & \(7.22\times 10^{-5}\) & \(5.43\times 10^{-5}\) \\ \hline \multirow{4}{*}{F7} & \multirow{4}{*}{0} & Mean & \(3.29\times 10^{-5}\) & \(3.3920\) & \(0.0682\) & \(0.0012\) & \(0.0023\) & \(1.03\times 10^{-4}\) & \(5.78\times 10^{-5}\) \\  & & Best & \(2.34\times 10^{-7}\) & \(0.0592\) & \(0.0023\) & \(2.11\times 10^{-4}\) & \(8.20\times 10^{-5}\) & \(1.16\times 10^{-6}\) & \(1.34\times 10^{-7}\) \\  & & Worst & \(1.41\times 10^{-4}\) & \(32.3393\) & \(0.4079\) & \(0.0031\) & \(0.0092\) & \(8.79\times 10^{-4}\) & \(3.78\times 10^{-4}\) \\  & & Std. Dev & \(3.40\times 10^{-5}\) & \(7.2993\) & \(0.0741\) & \(6.13\times 10^{-4}\) & \(0.0021\) & \(1.49\times 10^{-4}\) & \(6.68\times 10^{-5}\) \\ \hline \multirow{4}{*}{F8} & \multirow{4}{*}{\(-418.982\times n\)} & Mean & \(-5.59\times 10^{3}\) & \(-8.80\times 10^{3}\) & \(-3.84\times 10^{3}\) & \(-6.27\times 10^{3}\) & \(-1.09\times 10^{4}\) & \(-1.26\times 10^{4}\) & \(-1.25\times 10^{4}\) \\  & & Best & \(-6.81\times 10^{3}\) & \(-1.06\times 10^{4}\) & \(-4.43\times 10^{3}\) & \(-7.77\times 10^{3}\) & \(-1.26\times 10^{4}\) & \(-1.26\times 10^{4}\) & \(-1.26\times 10^{4}\) \\  & & Worst & \(-4.43\times 10^{3}\) & \(-7.08\times 10^{3}\) & \(-3.15\times 10^{3}\) & \(-4.66\times 10^{3}\) & \(-7.61\times 10^{3}\) & \(-1.26\times 10^{4}\) & \(-1.26\times 10^{4}\) \\  & & Std. Dev & \(445.5937\) & \(836.3389\) & \(236.3415\) & \(600.7231\) & \(1.70\times 10^{3}\) & \(0.2895\) & \(0.1582\) \\ \hline \multirow{4}{*}{F9} & \multirow{4}{*}{0} & Mean & 0.0075 & \(150.3165\) & \(34.7350\) & \(1.5057\) & \(0.0\) & \(0.0\) & \(0.0\) \\  & & Best & \(0.0\) & \(50.8095\) & \(0.034  
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline
**Func. ** & \(G_{m}\) & **Statistics** & **AOA** & **MFO** & **SCA** & **GWO** & **WOA** & **HHO** & **HHAOA** \\ \hline \multirow{4}{*}{F17} & \multirow{4}{*}{0.398} & Mean & 0.4080 & 0.3979 & 0.3993 & 0.3979 & 0.3979 & 0.3979 & 0.398 \\  & Best & 0.3983 & 0.3979 & 0.3979 & 0.3979 & 0.3979 & 0.3979 & 0.3980 \\  & Worst & 0.4434 & 0.3979 & 0.4062 & 0.3981 & 0.3979 & 0.3979 & 0.398 \\  & & Std. Dev & 0.0089 & 0.0 & 0.0016 & \(2.86\times 10^{-5}\) & 0.0 & 0.0 & 0.0 \\ \hline \multirow{4}{*}{F18} & \multirow{4}{*}{3} & Mean & \(8.4006\) & 3.0 & 3.0 & 3.0 & 3.0 & 3.0 & 3.0 \\  & Best & 3.0 & 3.0 & 3.0 & 3.0 & 3.0 & 3.0 & 3.0 \\  & Worst & 30.0 & 3.0 & 3.0 & 3.001 & 3.0001 & 3.0 & 3.0 \\  & Std.