## 5 Examples of Scheduling Optimization of Apron Support Vehicles
### Simulation 2: Configuration Optimization of Support Vehicle Quantity  
Through the optimization of support vehicle scheduling, the guarantee process of refueling trucks, oxygenation refilling trucks, and power vans for different numbers of aircraft can be obtained. For a certain number of guaranteed vehicles, by optimizing the guarantee process of guaranteed vehicles, the guarantee is improved. With the increase of working efficiency of the vehicle, the guaranteed time is greatly shortened, which is beneficial to the management of the apron vehicles. The relationship between the number of aircraft supported by multiple aircraft and the total time of the three support tasks is shown in Figure 6. It can be seen from the data in the figure that as the number of aircraft increases, the time to complete the three support tasks using the traditional support vehicle scheduling method gradually increases. When it exceeds 4 aircraft, the support time shows a linearly upward trend, and the support time of 6 aircraft has exceeded 120 min. The scheduling method based on the multi-layer coding genetic algorithm can greatly shorten the support time of the three tasks and improve support efficiency. In the actual aircraft support process, due to the limitations of facilities and equipment, such as runways, power supply air-conditioning vehicles, and combat methods, the maximum number of sorties in a single batch is six. According to the calculation, the average time to complete the single-aircraft to six-aircraft support operation after optimization is 74 min, which can meet the actual needs, and the average time before optimization is 100 min, which can also meet the training needs. However, with the further increase of the number of support aircraft, the traditional support model will definitely fail to meet the total time requirement. To shorten the support time, the airport's usual practice is to increase the \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Vehicle**} & \multicolumn{2}{c}{**Single-Aircraft before**} & \multicolumn{2}{c}{**Single-Aircraft after**} & \multicolumn{2}{c}{**Two-Aircraft before**} & \multicolumn{2}{c}{**Two-Aircraft after**} \\ \cline{2-9}  & **Utilization Ratio** & \(\mathbf{T_{t}}\) & **Utilization Ratio** & \(\mathbf{T_{t}}\) & **Utilization Ratio** & \(\mathbf{T_{t}}\) \\ \hline Re & 100\% & & 100\% & & 100\% & & 100\% & \\ Ox & 33.3\% & 55 & 33.3\% & 55 & 40\% & 85 & 66.7\% & 60 \\ Po & 18.2\% & & 18.2\% & & 23.5\% & & 36.4\% & \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Statistics of support vehicle utilization and completion time of three operations before and after scheduling optimization. number of support vehicles in the form that a group of support vehicles is responsible for two aircraft. Although requirement of the guaranteed time has been satisfied, the number of guarantee vehicles suffers a sharp increase, resulting in the difficulty of management and scheduling and increasing the safety risk of the apron. The scheduling operation method of the optimization algorithm, under the limit of the guaranteed number of vehicles, can be used to obtain the scheduling process in the shortest time through the optimization of the work sequence, thereby further shortening the guaranteed time and improving the guaranteed efficiency. In addition to the general requirement of total guarantee time, the utilization rate of guarantee vehicles is also an important indicator of optimization. The improvement of the utilization rate can reduce the number of guarantee resources, save costs, effectively reduce the idle time of equipment, and lead to a quick completion of the guarantee task. Through the above calculation, the utilization rates of the refueling truck, the oxygenation refilling truck, and the power van before and after the optimization are shown in Figures 7-9.