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

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...

Dynamic railway timetable rescheduling for multiple connected disruptions

Unexpected disruptions occur in the railways on a daily basis, which are typically handled manually by experienced traffic controllers with the support of predefined contingency plans. When several disruptions occur simultaneously, it is rather hard for traffic controllers to make rescheduling decisions, because (1) the predefined contingency...

Dynamic and robust timetable rescheduling for uncertain railway disruptions

Unexpected disruptions occur frequently in the railways, during which many train services cannot run as scheduled. This paper deals with timetable rescheduling during such disruptions, particularly in the case where all tracks between two stations are blocked for hours. In practice, a disruption may become shorter or longer than predicted. To...

Integrated timetable rescheduling and passenger reassignment during railway disruptions

During railway disruptions, most passengers may not be able to find preferred alternative train services due to the current way of handling disruptions that does not take passenger responses into account. To offer better alternatives to passengers, this paper proposes a novel passenger-oriented timetable rescheduling model, which integrates...

Reinforcement Learning in Railway Timetable Rescheduling

Real-time railway traffic management is important for the daily operations of railway systems. It predicts and resolves operational conflicts caused by events like excessive passenger boardings/alightings. Traditional optimization methods for this problem are restricted by the size of the problem instances. Therefore, this paper proposes a...

Dynamic and Robust Timetable Rescheduling for Uncertain Railway Disruptions

Unexpected disruptions occur frequently in railway systems, during which many train services cannot run as scheduled. This paper deals with timetable rescheduling during such disruptions, particularly in the case where all tracks between two stations are blocked for a few hours. In practice, the disruption length is uncertain, and a disruption...

Dynamic Passenger Assignment for Major Railway Disruptions Considering Information Interventions

Passenger assignment models for major disruptions that require trains to be<br/>cancelled/short-turned in railway systems are rarely considered in literature, although these models could make a significant contribution to passenger-oriented disruption timetable design/rescheduling. This paper proposes a dynamic passenger assignment model, where...

Railway timetable rescheduling for multiple simultaneous disruptions

Unexpected disruptions occur in the railways on a daily basis, which are<br/>typically handled manually by experienced trac controllers with the support of<br/>predened contingency plans. When several disruptions occur simultaneously, it is<br/>rather hard for trac controllers to make trac management decisions, because 1)<br/>the predened...

System-based Vulnerability Measures for Railway Systems

The issue of disruptions in railway systems attracts a growing attention due to its severity to the society. Mitigation strategies are proposed from different perspectives to reduce the system vulnerability resulting by disruptions. However, due to financial limitations, it is not realistic to realize all strategies in the real world. Thus, it...

Dynamic Passenger Assignment during Disruptions in Railway Systems

Passenger-oriented rescheduling problems receive increasing attention. However, the passenger assignment models used for evaluating the rescheduling solutions are usually simplified by many assumptions. To estimate passenger inconvenience more accurately, this paper establishes a dynamic passenger assignment model during disruptions, in which...