Discussions of the reschedule process of passengers, train operators and infrastructure managers in railway disruptions

Leng, Nuannuan; Weidmann, Ulrich

doi:10.1016/j.trpro.2017.12.034

Cited by 4 publications

(4 citation statements)

References 17 publications

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“…Leng and Weidmann ( 22 ) describe three stakeholders in the process of managing railway disturbances that cannot be overlooked: passengers, train operators, and infrastructure managers. Infrastructure managers are primarily responsible for the operational feasibility of the rescheduled schedule.…”

Section: Management Of Railway Operations From the Perspective Of The...mentioning

confidence: 99%

“…They also note that an important objective of passenger operators while managing interruptions is to minimize the total number of passengers affected by the interruption as well as the inconvenience to the affected passengers. Leng and Weidmann ( 22 ) add that passenger dissatisfaction is related to travel time in general, including time inside the train, waiting time, the number of transfers, and late arrival. Ghaemi et al ( 27 ) note that up to 1,000 passengers can wait for a train at a busy station during peak hours (that is, the time with the most significant demand), and passengers prefer a slightly delayed train to a canceled one.…”

Section: Management Of Railway Operations From the Perspective Of The...mentioning

confidence: 99%

See 1 more Smart Citation

Literature Review on Problem Models and Solution Approaches for Managing Real-Time Passenger Train Operations: The Perspective of Train Operating Companies

Marques

Moro

Ramos

2022

Transportation Research Record: Journal of the Transportation R

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This study presents a comprehensive review of different problem models for managing railway operations by problem-type classification. Railway terminology was used to identify the studies that encompass the existing body of knowledge. The 28 articles analyzed showed that existing studies are focused on the individual schedule components, such as rolling stock, schedules, crews, and passengers. Few studies have adopted a broader scope by covering several of those components. Two of the most popular approaches include the integer linear program and the mixed integer linear program variant. The difference between them is that integer programming uses discrete decision-making variable data, while mixed integer programming also admits continuous variable data. In contrast, few studies involve combining computational algorithms with human knowledge-based approaches. This analysis reveals that the most significant variables for managing disruptive events are related to verifying suppressed circulation and the discrete events of real-time traffic, such as departures and arrivals at stations.

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Section: Management Of Railway Operations From the Perspective Of The...mentioning

confidence: 99%

Section: Management Of Railway Operations From the Perspective Of The...mentioning

confidence: 99%

Literature Review on Problem Models and Solution Approaches for Managing Real-Time Passenger Train Operations: The Perspective of Train Operating Companies

Marques

Moro

Ramos

2022

Transportation Research Record: Journal of the Transportation R

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“…Disturbances in railway networks have a significant impact on the daily life of passengers. In railway disturbance management, there exist three major stakeholders: infrastructure managers, railway operators and passengers, each with diverse and potentially conflicting goals [11]. When rescheduling trains during a disturbance, the goals of an infrastructure manager are focused on the operational feasibility of the rescheduled timetable, while railway operators aim at minimizing operation costs [11].…”

Section: Introductionmentioning

confidence: 99%

“…In railway disturbance management, there exist three major stakeholders: infrastructure managers, railway operators and passengers, each with diverse and potentially conflicting goals [11]. When rescheduling trains during a disturbance, the goals of an infrastructure manager are focused on the operational feasibility of the rescheduled timetable, while railway operators aim at minimizing operation costs [11]. The liberalization of the European railway sector in recent years has compelled railway operators to increase the focus on satisfaction of passengers [2].…”

Section: Introductionmentioning

confidence: 99%

Parallel Computing for Multi-Objective Train Rescheduling

Josyula

Krasemann

Lundberg

2021

IEEE Trans. Emerg. Topics Comput.

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In railway traffic systems, it is essential to achieve a high punctuality to satisfy the goals of the involved stakeholders. Thus, whenever disturbances occur, it is important to effectively reschedule trains while considering the perspectives of various stakeholders. This typically involves solving a multi-objective train rescheduling problem, which is much more complex than its single-objective counterpart. Solving such a problem in realtime for practically relevant problem sizes is computationally challenging. The reason is that the rescheduling solution(s) of interest are dispersed across a large search tree. The tree needs to be navigated fast while pruning off branches leading to undesirable solutions and exploring branches leading to potentially desirable solutions. The use of parallel computing enables such a fast navigation of the tree. This paper presents a heuristic parallel algorithm to solve the multi-objective train rescheduling problem. The parallel algorithm combines a depth-first search with simultaneous breadth-wise tree exploration while searching the tree for solutions. An existing parallel algorithm for singleobjective train rescheduling has been redesigned, primarily, by (i) pruning based on multiple metrics, and (ii) maintaining a set of upper bounds. The redesign improved the quality of the obtained rescheduling solutions and showed better speedups for several disturbance scenarios.

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Digitalizing Railway Operations: An Optimization-Based Train Rescheduling Model for Urban and Interurban Disrupted Networks

Bafandkar,

Shafahi,

Eslami

et al. 2024

Digital Engineering

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Discussions of the reschedule process of passengers, train operators and infrastructure managers in railway disruptions

Cited by 4 publications

References 17 publications

Literature Review on Problem Models and Solution Approaches for Managing Real-Time Passenger Train Operations: The Perspective of Train Operating Companies

Literature Review on Problem Models and Solution Approaches for Managing Real-Time Passenger Train Operations: The Perspective of Train Operating Companies

Parallel Computing for Multi-Objective Train Rescheduling

Digitalizing Railway Operations: An Optimization-Based Train Rescheduling Model for Urban and Interurban Disrupted Networks

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