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

Research output: Contribution to journalResearch articleContributedpeer-review


  • Nikola Besinovic - , Delft University of Technology (Author)
  • Yihui Wang - , Beijing Jiaotong University (Author)
  • Songwei Zhu - , Beijing Jiaotong University (Author)
  • Egidio Quaglietta - , Delft University of Technology (Author)
  • Tao Tang - , Beijing Jiaotong University (Author)
  • Rob M.P. Goverde - , Delft University of Technology (Author)


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.


Original languageEnglish
Pages (from-to)10380-10394
Number of pages15
JournalIEEE Transactions on Intelligent Transportation Systems
Issue number8
Publication statusPublished - 1 Aug 2022
Externally publishedYes

External IDs

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



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