A Matheuristic for the Integrated Disruption Management of Traffic, Passengers and Stations in Urban Railway Lines

Publikation: Beitrag in FachzeitschriftForschungsartikelBeigetragenBegutachtung


  • Nikola Besinovic - , Technische Universität Delft (Autor:in)
  • Yihui Wang - , Beijing Jiaotong University (Autor:in)
  • Songwei Zhu - , Beijing Jiaotong University (Autor:in)
  • Egidio Quaglietta - , Technische Universität Delft (Autor:in)
  • Tao Tang - , Beijing Jiaotong University (Autor:in)
  • Rob M.P. Goverde - , Technische Universität Delft (Autor:in)


In big cities, the metro lines usually face great pressure caused by huge passengers demand, especially during peak hours. When disruptions occur, passengers accumulate quickly at stations. It is of great importance for dispatchers to take passenger flow control into consideration for the traffic management to ensure passengers' safety and to maintain their satisfaction. This paper proposes an integrated disruption management model, which incorporates train rescheduling and passenger flow control. In this model, the train services can be short-turned, cancelled and rerouted, while the number of passengers entering a station is managed by controlling the station gates with consideration of the capacities of platforms and trains. Moreover, the number of passengers arriving at a station is calculated according to the origin-destination matrices. The objectives are to recover the train operation to the original timetable as soon as possible and to minimize the waiting time of passengers outside the stations. With the interaction between train services, passengers and station gates, an iterative metaheuristic approach is proposed to solve the integrated disruption management problem. Based on the data of a Beijing metro line, numerical experiments are conducted to test the proposed algorithm. The results demonstrate the importance of integrated disruption management and the effectiveness of our solution method.


Seiten (von - bis)10380-10394
FachzeitschriftIEEE Transactions on Intelligent Transportation Systems
PublikationsstatusVeröffentlicht - 1 Aug. 2022
Extern publiziertJa

Externe IDs

ORCID /0000-0003-4111-2255/work/142246314



  • disruption, passengers, Railway, resilience, stations, trains