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

Abstract

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.

Repair part service level differentiation based on holding other parts shortage costs

“…For example, repairable items make up the majority of inventory value in the Caracas subway system (Díaz and Fu, 1997). This tendency has necessitated the study of safety stock policies for public transit systems (Sun et al ., 2020). Various approaches have been used in these settings including mathematical programming models for systems in rapid-speed trains (Lin et al ., 2017), double negative binomial approximations (Díaz and Fu, 1997) and monitoring approaches for buses (Corazza et al ., 2018).…”

Analysis of the location problem of emergency attendance teams for a railroad through optimization

“…The model proposed by us focuses on obtaining the optimal localization of maintenance teams providing emergency relief to failed trains on a railroad. Sun et al (2020) proposed a biobjective 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 the atom, the maximum failure response time, and maintenance guarantee rules.…”

“…Various authors studied maintenance issues in railroads with different approaches and in different locations such as Sweden, the United States, Greece, South Africa, the Netherlands, and China (Morant et al., 2014; Lidén, 2015; Xie et al., 2015; Xie and Ouyang, 2016; Argyropoulou et al., 2019; Toit et al, 2019; Tönissen and Arts, 2020; Sun et al., 2020; Wang et al., 2021; Zomer et al., 2021; Rahimi et al., 2022).…”

“…The maintenance service of a railroad involves the organization of a large amount of infrastructure which indeed causes the complexity of maintenance work. It is necessary to comply with integrated procedures, models, decision‐making tools, and the technical system to achieve a maintenance level compatible with operations and services (Sun et al., 2020). Despite this, little work has been done yet in the operational research area regarding infrastructure maintenance compared to train traffic operations (Lidén, 2015).…”

“…The maintenance network design aims to determine the location, the number, the guaranteed area, and the maintenance capability of maintenance points (Sun et al., 2020). Unplanned, or corrective, maintenance occurs when a train unit fails in the field.…”