# Simulation-Based Optimization of Transport Efficiency of an Urban Rail Transit Network
## 5 Conclusions and Future Research  
From the background of the rapid development of the urban rail transit network, this paper proposes the transport efficiency theory of the urban rail transit network system. It studies the interaction mechanism between capacity, passenger flow and efficiency, puts forward the shadow efficiency theory to express the quantitative relationship among them, and proposes a quantitative calculation method of system utility based on \"double time penalty\". The simulation experiments of single optimization strategy and combinatorial optimization strategy using DEA are designed, and the availability of these methods is proved by the case of the Beijing subway, and some optimization strategy combination rules are summarized. The results show that the departure interval is the restriction of technical efficiency, and the efficiency improvement brought by increasing departure density is more obvious with the increase in passenger volume. Improved departure density should be given priority to apply to crowded subway lines in morning peak hours, so as to boost the efficiency of the rail network. The cost of line construction contributes a large proportion of the total cost of Beijing subway, so we should give full play to the existing line capacity and give priority to changing operation organization to improve transport efficiency. The cost of newly built lines should be controlled, and the appropriate line system should be selected according to the function and passenger flow, to form an appropriate capacity supply and improve passenger service level under the constraint of a certain efficiency level. It is considered that the existing Beijing subway network can still improve the scale efficiency of the whole network system by adding new lines. However, attention should be paid to the hierarchy of lines and the upper limit.  
There are still some aspects to be extended in future work. Firstly, although a large amount of actual data of the Beijing subway are applied, some parameters are simplified in the simulation experiments, which need to be more detailed and accurate to be used in practical work. Secondly, this paper only studies the transport efficiency of the system during rush hours under normal conditions. We should further consider the transport efficiency under abnormal conditions such as operation interruption and large numbers of passengers, as well as how to save the input of transport resources and improve transport efficiency during off-peak hours. In addition, considering the historical evolution of cities and networks, how efficiency evolves over a long period of time is also worthy of in-depth study.  
Conceptualization, L.W. and F.L.; methodology, L.W. and B.H.; software, L.W., F.L. and C.Z.; validation, L.W. and Q.Z.; formal analysis, L.W. and F.L.; data curation, F.L. and B.H.; writing--original draft preparation, L.W., F.L. and B.H.; writing--review and editing, L.W. and F.L.; funding acquisition, Q.Z. All authors have read and agreed to the published version of the manuscript.  
This research was funded by Beijing Natural Science Foundation (L201013).  
Not applicable.  
The data presented in this study are available on request from the corresponding author.  
The authors thank everyone who contributed to this article.  
The authors declare no conflict of interest.