Scheduling overnight trains for improving both last and first train services in an urban subway network

Yuqiang Wang,Yuguang Wei,Pan Shang,Qi Zhang,Hua Shi

doi:10.1177/1687814019848920

Abstract

In most urban subway networks, passengers may make a transfer at night or in the early morning to arrive at their destinations. Given that passengers may confronted with transfer failure at night or long waiting in the morning, scheduling overnight trains is beneficial to both the last and first train services in the urban metro network, in particular, to minimize the number of failed transfer passengers in the last train service and the transfer waiting time for the first train service. Then, we formulate the overnight train scheduling problem as a mixed integer linear programming model based on a well-designed time-discretized space–time network. To handle large-scale applications, we decompose the proposed model into two space–time path-searching sub-problems and a semi-assignment problem through Lagrangian relaxation–based decomposition and solution framework. Finally, we adopt Beijing Subway Network as a practical case study. The results show that both the number of failed transfer passengers for las...

Highlights

MotivationThe development of the urban subway system has been thriving over the last decade, and many urban subway networks have become the most important transportation mode in cities[1] due to its security, wide accessibility, high-energy performance, reliable service, convenience, and low-carbon consumption.[2,3] Most subway systems are usually not operating for 24 h
The proposed model can be solved by a Lagrangian relaxation (LR) decomposition and solution framework, which is tested on a large-scale case of Beijing Subway Network
We propose a novel optimization model to schedule the overnight trains in an urban subway network

Summary

Motivation

The development of the urban subway system has been thriving over the last decade, and many urban subway networks have become the most important transportation mode in cities[1] due to its security, wide accessibility, high-energy performance, reliable service, convenience, and low-carbon consumption.[2,3] Most subway systems are usually not operating for 24 h. Article is ‘‘overnight trains’’: an overnight train is arranged by the operators to provide a transfer service for passengers who failed to transfer after the last train at night and passengers who waited for the first train in the morning for a long time, and stops at a specific non-service station during this period. Both XiErQi and GongZhufen are transfer stations. The proposed model can be solved by a Lagrangian relaxation (LR) decomposition and solution framework, which is tested on a large-scale case of Beijing Subway Network

Literature review

Objective function

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