## 4 Analysis of Experimental Results
### Simulation Experiment
#### 4.1.4 Comparative Analysis of Different Strategy Algorithms
Conversely, the global optimization strategy mainly affects the search accuracy of the algorithm, indicating the algorithm's ability to perform exploitation. In this article, these two capacities are effectively balanced by combining these two strategies to improve GEO, leading to improved algorithm performance. The theoretical numerical experiment for the revised algorithm is presented in this section. In Sections 4.2 and 4.3, specific application experiments are provided. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline
**Fun No.** & **Algorithm** & **Mean** & **Std** & **Time/s** & **Fun No.** & **Algorithm** & **Mean** & **Std** & **Time/s** \\ \hline \multirow{4}{*}{F1} & GEO & \(6.60\times 10^{-12}\) & \(6.80\times 10^{-12}\) & 0.8638 & & GEO & \(5.72\times 10^{-6}\) & \(1.52\times 10^{-5}\) & 0.8149 \\  & wGEO & \(3.37\times 10^{-169}\) & 0 & 0.9309 & F2 & wGEO & \(5.11\times 10^{-86}\) & \(1.21\times 10^{-85}\) & 0.7754 \\  & pGEO & \(1.08\times 10^{-292}\) & 0 & 0.9195 & & pGEO & \(4.81\times 10^{-154}\) & \(3.12\times 10^{-153}\) & 0.7696 \\  & IGEO & & 0 & 0.7280 & & IGEO & \(0\) & \(0\) & 0.9593 \\  & GEO & \(4.34\times 10^{-3}\) & \(6.04\times 10^{-3}\) & 0.8464 & & GEO & \(4.30\times 10^{-15}\) & \(7.03\times 10^{-16}\) & 0.8155 \\  & wGEO & 0 & 0 & 0.8268 & F4 & wGEO & \(8.88\times 10^{-16}\) & 0 & 0.8186 \\  & pGEO & 0 & 0 & 0.8384 & & pGEO & \(8.88\times 10^{-16}\) & 0 & 0.8310 \\  & IGEO & 0 & 0 & 0.8457 & & IGEO & \(8.88\times 10^{-16}\) & 0 & 0.8407 \\  & GEO & \(2.62\times 10^{0}\) & \(3.85\times 10^{-1}\) & 0.9738 & & GEO & \(1.77\times 10^{0}\) & \(2.69\times 10^{0}\) & 0.8146 \\ F5 & wGEO & \(9.00\times 10^{-1}\) & \(2.24\times 10^{-16}\) & 0.9290 & F6 & wGEO & 0 & 0 & 0.8040 \\  & pGEO & \(9.00\times 10^{-1}\) & \(2.24\times 10^{-16}\) & 0.9693 & & pGEO & 0 & 0 & 0.8040 \\  & IGEO & \(9.00\times 10^{-1}\) & \(2.24\times 10^{-16}\) & 0.9770 & & IGEO & 0 & 0 & 0.8406 \\  & GEO & \(4.16\times 10^{-1}\) & \(7.92\times 10^{-2}\) & 0.8811 & & GEO & \(8.18\times 10^{-21}\) & \(1.47\times 10^{-20}\) & 0.9774 \\ F7 & wGEO & \(8.03\times 10^{-3}\) & \(1.37\times 10^{-2}\) & 0.9259 & & F8 & wGEO & \(-3.75\times 10^{-1}\) & \(3.62\times 10^{-1}\) & 1.0186 \\  & pGEO & \(2.95\times 10^{-138}\) & \(2.09\times 10^{-137}\) & 0.9063 & & pGEO & \(-1.00\times 10^{0}\) & 0 & 0.9664 \\  & IGEO & 0 & 0 & 0.7688 & & IGEO & \(-1.00\times 10^{0}\) & 0 & 1.0303 \\  & GEO & \(1.30\times 10^{-59}\) & \(3.43\times 10^{-59}\) & 0.7909 & & GEO & \(1.50\times 10^{-125}\) & \(5.30\times 10^{-125}\) & 0.8167 \\ F9 & wGEO & \(1.22\times 10^{-182}\) & 0 & 0.8646 & F10 & wGEO & \(1.79\times 10^{-211}\) & 0 & 0.8387 \\  & pGEO & \(1.59\times 10^{-301}\) & 0 & 0.8199 & & pGEO & 0 & 0 & 0.7478 \\  & IGEO & 0 & 0.7652 & & IGEO & 0 & 0 & 0.5730 \\  & GEO & \(7.32\times 10^{-3}\) & \(7.56\times 10^{-3}\) & 1.3881 & & GEO & \(5.82\times 10^{-4}\) & \(6.30\times 10^{-4}\) & 1.4014 \\ F11 & wGEO & \(8.70\times 10^{-3}\) & \(8.62\times 10^{-3}\) & 1.1919 & F12 & wGEO & \(6.06\times 10^{-4}\) & \(4.79\times 10^{-4}\) & 1.2037 \\  & pGEO & \(3.47\times 10^{-31}\) & \(3.96\times 10^{-31}\) & 0.7713 & & pGEO & \(1.35\times 10^{-31}\) & \(2.21\times 10^{-27}\) & 0.8097 \\  & IGEO & 0 & 0 & 0.5874 & & IGEO & \(1.35\times 10^{-31}\) & \(2.21\times 10^{-27}\) & 0.7579 \\ \hline \end{tabular}
\end{table} 
Table 13: Comparison of test results for IGEO and various single-strategy algorithms.