Train rescheduling in a major disruption on a high-speed railway network with seat reservation

Shou-yi, Zhan; Wong, Stephen C. P.; Shang, Pan; Lo, S.M.

doi:10.1080/23249935.2021.1877369

Cited by 8 publications

(5 citation statements)

References 53 publications

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“…A time-expanded network model is devised to represent this problem, while the bi-objective optimization model is reformulated by the lexicographic method. Zhan et al [21] developed an integer linear programming model and decomposed it into sub-problems using the Alternating Direction Method of Multipliers (ADMM) algorithm. Jie et al [22] proposed a depth-first search crew recovery (DFSCR) method to deal with the real-time crew rescheduling problem.…”

Section: Literature Reviewmentioning

confidence: 99%

An Automatic Train Operation Based Real-Time Rescheduling Model for High-Speed Railway

Liu,

Xun

2023

Mathematics

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With the continuous development of the Automatic Train Operation (ATO) system in high-speed railways, automatic driving is progressively supplanting manual operations, ushering in a new era of predictability and reliability for high-speed railway transport. Concurrently, the advent of the ATO system provides a notable impact on real-time rescheduling during disruptions, as it equips dispatchers with precise insights into train operation statuses. This paper is dedicated to a thorough analysis of how the transition to automatic driving in train operations influences the real-time rescheduling model. Based on the distinctive impact of the ATO system on real-time rescheduling, we have proposed a mixed-integer linear programming model that combines train re-timing, reordering, and the minimization of passenger delays. To validate the effectiveness of our model, we present several experiments conducted using data from the Beijing–Shanghai high-speed railway line. The results unequivocally demonstrate that our ATO-based model significantly mitigates train delay time, demonstrating its practical value in optimizing high-speed railway operations.

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Section: Literature Reviewmentioning

confidence: 99%

An Automatic Train Operation Based Real-Time Rescheduling Model for High-Speed Railway

Liu,

Xun

2023

Mathematics

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“…The train running times under disruption are obtained from real-time information instead of being predetermined. Zhan et al [12] applied 'drive arc' to represent the train running in a segment between two stations. Principally, the drive arcs for a train in a segment are within a limited set, implying that the running time is a predetermined subject to a min-max range.…”

Section: Literature Reviewmentioning

confidence: 99%

Rescheduling Out-of-Gauge Trains with Speed Restrictions and Temporal Blockades on the Opposite-Direction Track

Liao

2023

Mathematics

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Out-of-gauge trains are trains with loading freight that exceeds the loading limitation border. Considering collision avoidance, the out-of-gauge trains have speed restriction of their own, and the trains running on the parallel track. Therefore, it is necessary to execute a train rescheduling procedure to rearrange the train paths of the out-of-gauge trains and the affected trains based on the fundamental timetable. For rescheduling the timetable, considering the blockades and the speed restrictions caused by the out-of-gauge trains, this paper proposed a time-space-state network representation for describing the out-of-gauge train rescheduling problem. A novel concept, speed allowance, is introduced to describe the train speed restriction due to the out-of-gauge trains. An integer programming model based on the time-space network is proposed to minimize the total train delay when running the out-of-gauge trains. The model can be solved by the rolling-time horizon approach for reducing computational time. A numerical example is conducted based on the conventional railway in China, demonstrating the solution performance of the model and the practical use of the methodology. Gurobi solver cannot obtain an optimal solution within 1 h when the planning-time horizon is greater than 120 min. With the rolling-time horizon approach, the rescheduled timetable can be obtained within 124 s for the 300 min planning-time horizon using 180 min rolling-time window.

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“…The adoption of an iterative process alone may not be sufficient because the TTP is a non-deterministic polynomialtime (NP)-hard problem for which an exact global optimum is hard to find [18]. Many methods have been proposed to solve this problem, including genetic algorithm [28]- [31], Lagrangian duality theory [32], alternating direction method of multipliers algorithm [33], and decomposition approach (DA) [34]- [36]. The DA has been widely adopted to solve TTPs because it can handle complex problems.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Constraint (33) ensures that if n is scheduled (b Sch n = 1), one TU is assigned to it. When the right side of Constraint (34) equals 0, v does not serve n; therefore, the left side of Constraint (34) should also equal 0.…”

Section: ; Xu Et Al 2018)mentioning

confidence: 99%

A Schedule-Based Model for Passenger-Oriented Train Planning With Operating Cost and Capacity Constraints

Xie

Shou-yi

Wong

et al. 2022

IEEE Trans. Intell. Transport. Syst.

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In the planning stage, train operators design timetables to serve passenger trips and a train circulation plan to support these timetables. These designs consider not only operating costs but also passenger convenience. In this study, we developed an optimization model for a new problem that focuses on timetabling and train-unit scheduling while also considering passenger itinerary choices in a schedule-based train system. This optimization model minimizes passenger travel costs within the constraints of a limited budget available for operating costs. The model is solved by an iterative heuristic that simulates the interaction between train operations and passenger itinerary choices. The heuristic solves the timetabling and train-unit scheduling problem using a decomposition approach to increase computational efficiency, while passenger loading is solved by a user-equilibrium passenger assignment model. An example based on the high-speed railway network in southern China was used to demonstrate the effectiveness of the proposed model and method.

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Train rescheduling in a major disruption on a high-speed railway network with seat reservation

Cited by 8 publications

References 53 publications

An Automatic Train Operation Based Real-Time Rescheduling Model for High-Speed Railway

An Automatic Train Operation Based Real-Time Rescheduling Model for High-Speed Railway

Rescheduling Out-of-Gauge Trains with Speed Restrictions and Temporal Blockades on the Opposite-Direction Track

A Schedule-Based Model for Passenger-Oriented Train Planning With Operating Cost and Capacity Constraints

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