## 3 Results
### Evaluation of the Scheduling Plan Result  
In this section, we have conducted several numerical experiments to verify the effectiveness of the proposed method. For the model, 24 scenarios were setup and the number of initial missions contained in these scenarios changed from 25 to 200, with an increase step of 25. The corresponding number of newly arrived missions changed from 5 to 75, with an increase step of 10. Simulation experiments were conducted in scenarios with 3, 4 and 5 satellite resources. The frequency of the insertion, reallocation, replacement and deletion operations for emergency missions in different scenarios was counted to obtain Figure 5.  
Figure 4: The ratio of missions with different priorities to all completed missions in the dynamic scheduling plan. Figure 5: The numbers of the four types of operations performed in dynamic scheduling under different simulation scenarios. (**a–d**) are the scheduling results for insertion, reallocation, replacement and deletion operations. Figure 3: The completed number and total number of missions with different priorities in the dynamic scheduling plan. It shows that for the same number of missions, as the number of satellite resources increases, the number of insertion operation notably increases, and the number of deleted missions decreases, which reduces the adjustment to the initial scheduling plan. The number of reallocation operation performed for missions is generally higher than that of replacement operation, which reduces the probability of deleting the initial missions. The model evaluation function defined in Section 2.5 was performed to evaluate the scheduling results for 24 different scenarios, and the computational complexity was measured using elapsed CPU time (Table 13). The evaluation indicators of the scheduling plans indicate that for the same number of satellite resources, as the number of missions increases, the mission completion rate and priority execution rate exhibit decreasing trends. When the number of missions is less than 100, the mission completion rate and the priority execution rate are both greater than 0.8 in different scenarios, achieving a better scheduling effect. In the scenario with 25 initial missions, five newly arrived missions and five satellites, the maximum value of the evaluation function is 11.40. Because the numbers of insertion and reallocation operations in this scenario are 3 and 2, respectively, the scheme change rate is small. However, when the number of missions is more than 100, the results for each evaluation indicator are poor. We can see that the running time of initial scheduling generally increases with the number of missions, with a maximum of 564.72 s. In contrast to the initial scheduling, the computation time for the dynamic scheduling are quite short, because the satellite resources are allocated based on initial scheduling and mission priority. However, the running time increases significantly with mission size because more different operations are needed in the iteration. It is worth mentioning that the mission priority execution rate is always larger than the mission completion rate, this phenomenon illustrates that the proposed method increases the execution probability of high-priority missions. The above results show that the proposed model is practicable and can meet the need of real-time processing with low time cost, especially for solving small and medium-scale problems. However, due to the mission priority set in this paper, the resource allocation strategy may be unfair, so some processes may wait for a long time. From the  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{ \begin{tabular}{c} **Number of Initial** \\ **Missions** \\ \end{tabular}  } & \multirow{2}{*}{ \begin{tabular}{c} **Number of** \\ **Newly** \\ **Arrived** \\ **Missions** \\ \end{tabular}  } & \multirow{2}{*}{ \begin{tabular}{c} **Mission** \\ **Satellite** \\ \end{tabular}  } & \multirow{2}{*}{ \begin{tabular}{c} **Mission** \\ **Completion** \\ **Rate** \\ \end{tabular}