Maintenance Decision-Making of an Urban Rail Transit System in a Regionalized Network-Wide Perspective

• Main Authors: Baofeng Sun, Jiaojiao Liu, Junyi Hao, Xiuxiu Shen, Xinhua Mao, Xianmin Song
• Format: Article
• Language: English
• Published: MDPI AG 2020-11-01
• Series: Sustainability
• Subjects: urban rail transit; regionalized network-wide maintenance; integrated network design model; Monte-Carlo simulation; scenario analysis
• Online Access: https://www.mdpi.com/2071-1050/12/22/9734

The networked operation of Urban Rail Transit (URT) brings the new challenge of network-wide maintenance. This research focuses on the URT Network-Wide Maintenance Decision-Making Problem (URT-NMDP), including regionalized maintenance network design and maintenance resource allocation. In this work, we proposed a bi-objective integer programming model that integrates the characteristics of set coverage and P-median models, resulting in the regionalized maintenance network design model. Some critical factors are considered in the model, such as the importance of node, the maximum failure response time, and maintenance guarantee rules. We designed a NSGA-II based algorithm to solve the model. Moreover, due to the uncertainty of failures in the URT network, we developed the method of allocating maintenance resources based on Monte Carlo simulation to strengthen the reliability of the regionalized maintenance network. With the model and algorithm presented in this work, we obtained Pareto optimal solutions of URT-NMDP, i.e., URT network-wide maintenance planning schemes, which include the number and location of maintenance points, the allocation of demand points, and the amount of maintenance units. Finally, a real-world case is studied to evaluate the operating performance of these schemes for verifying the method in our paper. The results of the case study demonstrate that the reasonable and tested-in-practice maximum failure response time is the precondition for the efficient URT maintenance network. The maintenance scheme considered the weighted importance of node shows the optimal performance, with the shortest overall maintenance path and the minimum average failure response time and investment cost on maintenance resources.