Yihong Chang
State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China
Ru Niu
State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China
Yihui Wang
State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China
Xiaojie Luan
Section Transport Engineering and Logistics, Delft University of Technology, Delft, the Netherlands
Marcella Samà
Deparment of Engineering, Roma Tre University, Rome, Italy
Andrea D’Ariano
Deparment of Engineering, Roma Tre University, Rome, Italy
Download articlePublished in: RailNorrköping 2019. 8th International Conference on Railway Operations Modelling and Analysis (ICROMA), Norrköping, Sweden, June 17th – 20th, 2019
Linköping Electronic Conference Proceedings 69:17, p. 253-269
Published: 2019-09-13
ISBN: 978-91-7929-992-7
ISSN: 1650-3686 (print), 1650-3740 (online)
Disruptions in urban rail transit systems usually result in serious incidents due to the high density and the less flexibility. In this paper, we propose a novel mathematical model for handling a complete blockage of the double tracks for 5-10 minutes, e.g., lack of power at a station, where no train can pass this area during the disruption. Under this disruption scenario, train services may be delayed or cancelled, some rolling stock may be short-turned at the intermediate stations with either single or double crossovers. To ensure the service quality provided to passengers, the back-up rolling stock inside depots may also be put into operation depending on the consequences of the disruptions. Thus, the number of rolling stock in the depot is considered. We discuss the disruption management problem for urban rail transit systems at a macroscopic level. However, operational constraints for the turnaround operation and for the rolling stock circulation are modelled. A mixed-integer non-linear programming (MINLP) model, which can be transformed into mixed-integer linear programming (MILP) problem, is proposed to minimize the train delays and the number of cancelled train services as well as to ensure a regular service for passengers, while ad-hering to the departure and arrival constraints, turnaround constraints, service connection constraints, inventory constraints, and other relevant railway constraints. Existing MILP solvers, e.g. CPLEX, are adopted to obtain near-optimal solutions. Numerical experiments are conducted based on real-world data from Beijing subway line 7 to evaluate the effectiveness and efficiency of the proposed model.
Urban rail transit, Train rescheduling, Complete blockage, Short-turn, Rolling stock circulation