Integrated timetable rescheduling and rolling stock reassignment for an urban rail transit system during large-scale disruptions

Akhlaghi, Motahare-Sadat; Reisi-Nafchi, Mohammad; Moslehi, Ghasem

doi:10.22068/ijrare.315

Volume 10, Issue 1 (6-2023) IJRARE 2023, 10(1): 29-44 | Back to browse issues page

‎ 10.22068/ijrare.315

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Akhlaghi M, Reisi-Nafchi M, Moslehi G. Integrated timetable rescheduling and rolling stock reassignment for an urban rail transit system during large-scale disruptions. IJRARE 2023; 10 (1) :29-44
URL: http://ijrare.iust.ac.ir/article-1-315-en.html

Integrated timetable rescheduling and rolling stock reassignment for an urban rail transit system during large-scale disruptions

Motahare-Sadat Akhlaghi

, Mohammad Reisi-Nafchi

, Ghasem Moslehi

Department of Industrial and Systems Engineering, Isfahan University of Technology, Isfahan 84156-83111, Iran

Abstract: (507 Views)

Railway transport systems are critical for the economy's competitiveness and the mobility of people and goods. These systems are increasingly important in urban public transportation networks because of their high capacity, punctuality, and low energy consumption. In actual operations, unavoidable disruption often delays the original train timetable. When trains are delayed, dispatchers adapt the impacted train timetables to the perturbations. This paper captures real-time traffic management using a mixed-integer linear programming (MILP) model. Flexible stopping is innovatively integrated with delaying and canceling to reschedule a timetable during railway disruptions. The model presented in this paper also considers the assignment of rolling stock (RS) to courses. A real-world instance of London's new Elizabeth line, UK, was used to test the proposed model based on several disruption scenarios. The Elizabeth Line (formally known as Crossrail) will stretch more than 96 kilometers from Reading and Heathrow in the west through central tunnels across to Shenfield and Abbey Wood in the east. The RAS2022 competition provides these problem instances. The model was solved with the Gurobi solver. The computational results from the Gurobi solver show that the performance of the proposed model is appropriate for solving the problem. The model can solve all three evaluation problem instances with good quality within the time limit. Our experimental results found that delay is preferable to canceling a course in our model.

Keywords: railways, real-time traffic management, flexible stopping, rolling stock assignment, track assignment

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Type of Study: Research | Subject: Railway Transportation