# Simulation-Based Optimization of Transport Efficiency of an Urban Rail Transit Network
## 4 Result Analysis
### DEA Analysis of Simulation Results
If the inputs are increased, waste will be generated, resulting in a decrease in the scale efficiency of the rail network. However, the pure technical efficiency of scheme 13 is less than 1, which indicates that at the current technical level, the input scale is low and the transport efficiency of the rail network cannot be fully exerted. Therefore, some inputs can be correspondingly increased to improve the output, thus improving the transport efficiency of the rail network, that is, the scale efficiency is increasing. Comparing scheme 13 with scheme 16 (original passenger flow, deletion of Line 6, an increase of 30 s in the morning peak departure interval of Line 2), it can be seen that under the same passenger flow level and rail network scale, the train departure intervals become the bottleneck of network transport efficiency. When the departure interval is small (departure density is high) and the transport capacity is large, the network transport efficiency is higher. Therefore, higher departure density should be allocated to give full play to the efficiency of the rail network scale when necessary. 2. DEA evaluation results of an increasing passenger flow scale by 10%  
The schemes under the scale of increasing passenger flow by 10% include schemes 2, 5, 8, 11, 14, 17, 20 and 23, and the DEA evaluation results and calculated network efficiency are shown in Table 10 below. Scheme 11 is the benchmark scheme, that is, the Changping Line and Line 6 are deleted, and the departure intervals of Line 2 during morning rush hours are increased by 30 s.  
As can be seen from the above table, the scale reward of scheme 2 (original rail network, original departure density and a 10% increase in passenger flow scale) and scheme 20 (deleting the Changping Line/constructing Line 6, original departure density and increasing passenger flow scale by 10%) is unchanged, while the scale reward of scheme 14 (deleting Line 6/constructing the Changping Line, original departure density and increasing passenger flow scale by 10%) is increasing, and the scale rewards of the rest of the schemes decrease gradually. 3. DEA evaluation results of decreasing passenger flow scale by 10%  
The schemes under the scale of decreasing passenger flow by 10% include schemes 3, 6, 9, 12, 15, 18, 21 and 24, and the DEA evaluation results and calculated network efficiency are shown in Table 11 below. Scheme 12 is the benchmark scheme, that is, the Changping Line and Line 6 are deleted, and the departure intervals of Line 2 during morning rush hours are increased by 30 s. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Optimum Scheme**} & \multirow{2}{*}{**Technical Efficiency**} & \multicolumn{2}{c}{**DEA Evaluation Results**} & \multicolumn{3}{c}{**Network Efficiency**} \\  & & **Pure Technical** & **Scale** & **Scale Reward** & **Input 1** & **Output 2** & **Shadow Efficiency** \\ \hline
2 & 1 & 1 & 1 & unchanged & 11,310,210 & 2,880,320 & 0.25466 \\
5 & 0.961627 & 1 & 0.961627 & decreased by degrees & 11,273,050 & 2,481,860 & 0.22015 \\
8 & 0.823666 & 1 & 0.823666 & decreased by degrees & 37,162.8 & 445,540 & 11.98905 \\
11 & 0.762984 & 1 & 0.762984 & decreased by degrees & 0 & 0 & - \\
14 & 0.841672 & 0.998505 & 0.842932 & increased by degrees & 4,686,273 & 726,970 & 0.15512 \\
17 & 0.785603 & 1 & 0.785603 & decreased by degrees & 4,649,110 & 305,350 & 0.06567 \\
20 & 1 & 1 & 1 & unchanged & 6,661,103 & 2,445,490 & 0.36713 \\
23 & 0.952581 & 1 & 0.952581 & decreased by degrees & 6,623,940 & 2,055,940 & 0.31038 \\ \hline \hline \end{tabular}  
* The input refers to the increased cost (unit: CNY) compared with the benchmark scheme. 2 The output refers to the saved travel time (unit: CNY) compared with the benchmark scheme.  
\end{table} 
Table 10: DEA evaluation results of each program for a 10% increase in passenger flow scale.