Application of an iterative framework for real-time railway rescheduling

Dollevoet, Twan; Huisman, Dennis; Kroon, Leo; Veelenturf, Lucas P.; Wagenaar, Joris

doi:10.1016/j.cor.2016.08.011

Cited by 49 publications

(19 citation statements)

References 17 publications

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“…These works also show the interrelation between these problems, where rolling stock rescheduling is generally performed after finding an updated timetable and is succeeded by steps such as crew rescheduling and the rescheduling of the shunting plans at the stations. Dollevoet et al (2017) show that Notes. The initial delay is present on trip t 1 , and a dashed line indicates that a trip is delayed.…”

Section: Related Literaturementioning

confidence: 96%

Reducing Passenger Delays by Rolling Stock Rescheduling

Hoogervorst

Dollevoet

Maróti

et al. 2020

Transportation Science

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Delays are a major nuisance to railway passengers. The extent to which a delay propagates, and thus affects the passengers, is influenced by the assignment of rolling stock. We propose to reschedule the rolling stock in such a way that the passenger delay is minimized and such that objectives on passenger comfort and operational efficiency are taken into account. We refer to this problem as the passenger delay reduction problem. We propose two models for this problem, which are based on two dominant streams of literature for the traditional rolling stock rescheduling problem. The first model is an arc formulation of the problem, whereas the second model is a path formulation. We test the effectiveness of these models on instances from Netherlands Railways (Nederlandse Spoorwegen). The results show that the rescheduling of rolling stock can significantly decrease passenger delays in the system. Especially, allowing flexibility in the assignment of rolling stock at terminal stations turns out to be effective in reducing the delays. Moreover, we show that the arc formulation–based model performs best in finding high-quality solutions within the limited time that is available in the rescheduling phase.

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Section: Related Literaturementioning

confidence: 96%

Reducing Passenger Delays by Rolling Stock Rescheduling

Hoogervorst

Dollevoet

Maróti

et al. 2020

Transportation Science

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“…For each place of S, we denote [L i j , q i j e , H i j ] the lower bound of the time window, the expected sojourn time of tokens, and the upper bound of the time window, respectively. https://www.indjst.org/ Unpredictable events as small disruptions (such as malfunctions or absence of personnel) and significant disruptions (such as significant and particularly damaging external accidents; train and infrastructure failures) are considered in (15) and (16)(17)(18)(19) . Both types of events necessarily result in the invalidity of the train time table.…”

Section: Collected Data From Tnrc Companymentioning

confidence: 99%

Robust control strategies facing disturbances in Railway Transport Networks

Mhalla¹,

Gaied²,

Lefebre³

2021

IJST

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Objectives:The key objective of this present article is the presentation of a control strategy which consists to compensate the disturbance as soon as it is observed. The main purpose of the proposed control strategy is to guarantee the respect of railway scheduling. The novel strategy allows compensating temporal disruption as soon as it is observed in order to avoid the time constraint violation and to respect planned scheduling. Methods: An algorithm that amends the measured disturbances by compensating the disruption along the mono-synchronized paths is presented. The proposed algorithm allows computing the available control margin for every controllable place. Findings: The main impartial is to compensate partially or totally the disturbance so as to avoid time constraint violation in railway transport networks. In these networks, time may be a significant parameter because it encompasses constraints to avoid adverse events. The temporal constraints which will arise on the railway network may degrade the planed schedules and consequently affect the availability of transportation systems. This leads to many problems in the decision and optimization of the studied transport systems. Novelty/Applications: This paper is devoted to the modeling and robust control of the Tunisian railway network. In this context, a novel robustness strategy is developed to compensate the time disruption in railway networks and to preserve the planned schedule.

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“…The problem of optimizing real-time decisions in freight systems has been the subject of recent study in contexts other than aid delivery, such as for ship liners by Li et al (2016), for high speed trains by Zhan et al (2015), for railways by Dollevoet et al (2017), for high frequency transit by Sánchez-Martínez et al (2016), for express urban pick-up and delivery by Ferrucci and Bock (2014) and for buses by Berrebi et al (2015). Although all these studies are insightful about optimizing real-time decisions in transportation systems, their objectives are different from objectives pursued for the humanitarian aid delivery.…”

Section: Literature Reviewmentioning

confidence: 99%

A Probabilistic Framework for Optimizing Real-time Decisions in Humanitarian Aid Delivery Systems

Yousefzadeh

2020

Preprint

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This paper presents a computationally efficient model for optimizing real-time decisions in humanitarian aid delivery systems. Our formulation models a hierarchical system and is a mixed integer, probabilistic, non-linear and non-concave optimization problem. The proposed model considers the costs and probabilistic nature of transfer times and maximizes the reliability of the system using the available budget. We account for late deliveries using a nonlinear penalty function. We also propose an algorithm that uses a directed acyclic graph to deal with the discrete variables in tandem with a homotopy method for optimizing the continuous variables. We then offer a pruning method to eliminate the cost inefficiencies in the system. The effectiveness of formulation is examined in some numerical examples in development.

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Application of an iterative framework for real-time railway rescheduling

Cited by 49 publications

References 17 publications

Reducing Passenger Delays by Rolling Stock Rescheduling

Reducing Passenger Delays by Rolling Stock Rescheduling

Robust control strategies facing disturbances in Railway Transport Networks

A Probabilistic Framework for Optimizing Real-time Decisions in Humanitarian Aid Delivery Systems

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