## 4 Numerical Analysis
### Decision Evaluation
#### 4.3.2 Comprehensive Analysis of Location  
To compare the most available decision results under different maximum overcoverages, a comprehensive analysis is conducted for the three siting decisions corresponding to the shortest rescue mileage in Table 4, as shown in Table 6. The distribution of emergency facility points corresponding to different siting decisions is shown in Figure 6.  
As shown in Table 6 and Figure 6, the 32 emergency facility points of location decision 1 can cover all the demand points, and the demand points are overcovered no more than 2 times, as shown in location decision 3. As shown in Figure 7a, the objective of minimizing the total emergency rescue mileage of location decision 1 is obtained after the 691 st iteration of the population. The algorithm converges for the first time in the 31 st iteration, for the second time in the 88 th iteration and for the third time in the 421 st iteration; the relationship between the number of railway hazardous-cargo emergency facilities and the number of iterations shows that the number of railroad hazardous-cargo emergency facilities decreases in the first 690 iterations and gradually converges with the optimal solution. That is, the number of RDGT emergency facilities with the smallest total emergency rescue mileage. Figure 5: Topology of the emergency location network under different robustness levels. The red dotted line in the figure represents the demand point service relationship. (**a**) \(\Omega=6\); (**b**) \(\Omega=16\). \begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Location Decision 1** & **Location Decision 2** & **Location Decision 3** \\ \hline Maximum overcoverage & 2 & 3 & 4 \\ \hline Number of emergency facility sites & 32 & 40 & 41 \\ \hline  & & Changchun, Siping, Tieling, Benxi, Fuixin, Dandong, Huludao, Zhoushuizi, Jiahuo, Tonghua, Baisheng, Tonghua, Baisan, Liaoyuan, Mehekou, Shanhaiguan, Tongliao, South, Wuzumuchin, Mehekou, Tonghua, Baishan, Wuzumuchin, Baicheng, Chaoyangchuan, Siiheyong, Taipingchuan, Daanbei, Daguntun, Zalut, Gaoshanzi, Gaizhou, Qipan, Yebeshou, Shuangliao, Jinshanwan, Zhushua, Linshengbao, Liushutun, Panshui, Wukeshu & Changchun, Jilin West, Siping, Fuxin South, Sijatun, Wafangdian, Jinzhou, Shanhaiguan, Taibanguan, Mahekou, Shanhaiguan, Tongliao, Ulanhot, Chifeng, Wujumuqin, Chifeng South, Tongliao, Dujia, Huadian, Qiandian, Beitai, Kuandian, Chaoyangchuan, Chayangchuan, Yuguo, Siiheyong, Dashiqiao, Wengguan Tun, Gaoshanzi, Huilhue, Daan North, Taipingchuan, Lalatun, Hongshi, Ishii, Zalut, Zhangtaizi, Shuangliao, Jinshanwan, Wukeshu, Liushun Tun, Chaoyang West, Nongan \\ \hline Emergency rescue mileage & 682.89 km & 625.10 km & 672.83 km \\ \hline Optimal solution iteration number & 691 & 622 & 1052 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Comparison of the results of solving elliptic robust models with different maximum overcoverages. Figure 6: Emergency location network scatter diagram. As shown in Table 6 and Figure 6, the 40 emergency facility points of site selection decision 2 can cover all the demand points as well as the demand point's overcoverage  
Figure 7: Relationship between the number of iterations and the total mileage of emergency rescue and the number of emergency facilities. (**a**) Location decision 1. (**b**) Location decision 2. (**c**) Location decision 3.  
no more than three times. As shown in Figure 7b, the objective of minimizing the total emergency rescue mileage of site selection decision 2 is obtained after the 622 nd iteration of the population. The algorithm converges for the first time during the 97 th iteration, and the optimal solution is obtained after several iterations of convergence over 503 iterations. From the relationship between the number of RDGT emergency facilities and the number of iterations, we can see that in the first 621 iterations, the number of RDGT emergency facilities keeps decreasing and gradually converges with the optimal solution.