Railway disruption

A bi-level rescheduling algorithm

Conference Paper (2019)
Author(s)

G. Cavone (University of Bari, TU Delft - Team Bart De Schutter)

L. Blenkers (Student TU Delft)

AJJ Van Den Boom (TU Delft - Team Bart De Schutter)

Mariagrazia Dotoli (University of Bari)

C Seatzu (University of Cagliari)

BHK De Schutter (TU Delft - Team Bart De Schutter, TU Delft - Delft Center for Systems and Control)

Research Group
Team Bart De Schutter
DOI related publication
https://doi.org/10.1109/CoDIT.2019.8820380
More Info
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Publication Year
2019
Language
English
Research Group
Team Bart De Schutter
Pages (from-to)
54-59
ISBN (electronic)
978-1-7281-0521-5

Abstract

The real-time rescheduling of railway traffic in case of unexpected events is a challenging task. This is mainly due to the complexity of the railway service, which has to ensure safety, punctuality, and efficiency to customers by respecting timetable, framework, and resources constraints. Most of the available researches focus on short delays (i.e., disturbances). Approaches typically rely on simplified macroscopic models for large-scale systems or detailed microscopic models for one or a few lines, due to the long computation time required for solving the rescheduling problem. Only a small number of works consider rescheduling in case of long delays (i.e., disruptions) and all of them are also based on either a macroscopic or a microscopic model. This research focuses on disruptions and aims at filling the gap between macroscopic and microscopic modelling by proposing an innovative bi-level rescheduling algorithm based on a mesoscopic Mixed Integer Linear Programming (MILP) model. The technique allows obtaining a feasible rescheduled timetable in a short computation time respecting not only timetable and safety constraints (typical of macroscopic models) but also capacity and ordering constraints for the disrupted stations (typical of microscopic models). The bi-level algorithm first solves the macroscopic MILP rescheduling problem and then, considering the cancellation and non-admissible platform assignments results, it solves a mesoscopic MILP rescheduling problem. This allows to significantly reduce the search space and consequently the computation time. The method is tested for the rescheduling of the Dutch railway traffic in case of a full blockade between two consecutive stations.

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