# Research on Demand-Based Scheduling Scheme of Urban Low-Altitude Logistics UAVs
## 4 Example Verification and Analysis
### Analysis of Algorithm Parameters  
When solving drone demand, drone speed, load, and working hours will affect drone demand, as will the number of batteries at the distribution point, the number of drones, and other parameters. In this paper, controlled experiments were carried out to analyze the influence of the number of backup batteries, working hours, and charging time on drone demand when the number of drones changes. Keep the settings of the other parameters as shown in Tables 2 and 3 unchanged. The number of drones is set to be 20, 30, 40, 50, 60, 70, and 80, respectively. The number of backup batteries is 10, 15, 20, 25, and 30, respectively. Multiple controlled experiments were conducted under the same conditions as other parameter settings and the airspace environment. The delivery costs required for the two different routes in each case were obtained, and the results are shown in Figure 6. The left side represents the RN route, the right side represents the BN route, and the unfilled hollow circle indicates the delivery cost under this condition, while the filled circle indicates that the lowest delivery cost has been reached at this time. It can be seen from Figure 6 that the delivery cost is related to the changes in the number of drones and the number of backup batteries. This cost generally shows a downward trend and then rises. When the number of drones is 70 and the number of backup batteries is 15, the delivery cost of the RN route is the lowest. The BN route has the lowest delivery cost when the number of drones is 70 and the number of backup batteries is 20. Therefore, these numbers of drones and backup batteries can be considered when the actual logistics drones are delivered. Keep the other parameters as shown in Tables 2 and 3 unchanged. The number of drones is set to be 20, 30, 40, 50, 60, 70, and 80, respectively. The working hours are 10 min, 20 min, 30 min, and 40 min. Multiple controlled experiments were carried out under the same conditions as other parameter settings and the airspace environment. The delivery costs of the two different routes in each case were obtained, and the results are shown in Figure 7. The left side represents the RN route, the right side represents the BN route, and \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Algorithm** & **RN/BN Delivery Cost** & **RN/BN Delivery Time** \\ \hline Delivery distance priority & 2207.14/1705.75 & 5 h 48 min 37 s/5 h 44 min 47 s \\ Delivery package volume priority & 2172.33/1737.61 & 5 h 37 min 33 s/5 h 47 min 32 s \\ Random delivery & 2236.30/1654.93 & 5 h 45 min 43 s/5 h 50 min 32 s \\ Standard simulated annealing & 2281.58/1713.23 & 5 h 41 min 5 s/5 h 46 min 44 s \\ Improved simulated annealing & 2089.11/1626.37 & 5 h 36 min 33 s/5 h 47 min 44 s \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Results of drone scheduling schemes under different algorithms. \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & **Maximum Value** & **Minimum Value** & **Average Value** & **Variance** \\ \hline RN & 2326.42 & 2236.30 & 2272.81 & 361.64 \\ BN & 1758.34 & 1654.93 & 1699.04 & 428.72 \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Random delivery statistics results. the unfilled hollow circle indicates the delivery cost under this condition, while the filled circle indicates that the lowest delivery cost has been reached at this time. It can be seen from Figure 7 that the delivery cost is related to the changes in the number of drones and working hours. This cost generally shows a trend of decreasing and then rising. When the number of drones is 70 and the working time is 30 min, the delivery costs of both the RN route and the BN route are the lowest. Therefore, when the actual logistics drones are used for distribution, these results of drone numbers and working time can be considered. Keep the other parameters as shown in Tables 2 and 3 unchanged. The number of drones is set to be 20, 30, 40, 50, 60, 70, and 80, respectively. The charging times are 1 h, 1.5 h, 2 h, and 2.5 h, respectively.