Solving cyclic train timetabling problem through model reformulation: Extended time-space network construct and Alternating Direction Method of Multipliers methods

Zhang, Yongxiang; Peng, Qiyuan; Yao, Yu; Zhang, Xin; Zhou, Xuesong

doi:10.1016/j.trb.2019.08.001

Cited by 81 publications

(19 citation statements)

References 78 publications

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“…Second, the MILP model and the heuristic algorithm GSAHA proposed in this paper can be further developed to consider different station types, such as the terminal station where trains need to perform the turnaround movement that makes the train platforming problem more complicated [42,43]. ird, the train movements at the stations can be viewed as a set of space-time paths, and thus more efficient dual decomposition methods could be developed accordingly [7,44,45]. Fourth, more efficient solution algorithms can be developed for the simultaneous reoptimization of several interconnected railway stations in a railway line or even a regional railway network with more complicated structure so that the joint optimization of delay situations and train timetabling problems can be achieved [8,19,27,[46][47][48][49].…”

Section: Discussionmentioning

confidence: 99%

“…We refer the readers to Assad [3], Cordeau [4], and Lusby et al [2] for excellent surveys on the related optimization methods. In general, train timetabling stage can determine the arrival and departure times of the trains at each of the visiting stations from an aggregate perspective [5][6][7][8]. Train operations at the stations, including the train routing on the arrival and departure routes and the train platform assignment decisions, are usually optimized by solving the train platforming problem [8].…”

Section: Introductionmentioning

confidence: 99%

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A Fast Approach for Reoptimization of Railway Train Platforming in Case of Train Delays

Zhang

Zhong

Yin

et al. 2020

Journal of Advanced Transportation

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Train platforming is critical for ensuring the safety and efficiency of train operations within the stations, especially when unexpected train delays occur. This paper studies the problem of reoptimization of train platforming in case of train delays, where the train station is modeled using the discretization of the platform track time-space resources. To solve the reoptimization problem, we propose a mixed integer linear programming (MILP) model, which minimizes the weighted sum of total train delays and the platform track assignment costs, subject to constraints defined by operational requirements. Moreover, we design an efficient heuristic algorithm to solve the MILP model such that it can speed up the reoptimization process with good solution precision. Furthermore, a real-world case is taken as an example to show the efficiency and effectiveness of the proposed model and algorithm. The computational results show that the MILP model established in this paper can describe the reoptimization of train platforming accurately, and it can be solved quickly by the proposed heuristic algorithm. In addition, the model and algorithm developed in this paper can provide an effective computer-aided decision-making tool for the train dispatchers in case of train delays.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Fast Approach for Reoptimization of Railway Train Platforming in Case of Train Delays

Zhang

Zhong

Yin

et al. 2020

Journal of Advanced Transportation

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“…For example, the probability of station failures can be determined by historical data, and the reliability of a URT network can be evaluated from the travel quality of passengers. In the future, the reliability of URT operations can be further improved by combining the connectivity reliability analysis with the optimization of train timetabling (Zhang et al [29,30]) and rolling stock scheduling (Zhong et al [31]) of URT networks.…”

Section: Discussionmentioning

confidence: 99%

Connectivity Reliability on an Urban Rail Transit Network from the Perspective of Passenger Travel

et al. 2019

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Under the background of urbanization and the rapid development of urban rail transit (URT), serious attention has been focused on URT network reliability in recent years. In this work, in order to measure network reliability, three indicators are constructed based on passengers' tolerable travel paths, passenger travel efficiency and passenger travel realization on a URT network. The passenger tolerability coefficient, which is the ratio of passengers' tolerable travel time to the shortest possible travel time, is proposed and added to the indicators. It reflects passengers' behavior with respect to choice of travel paths. The ratio of affected passenger volume (RAPV) is proposed to identify important stations. Finally, the connectivity reliability of Wuhan's subway network is analyzed by simulating attacks on stations. The results show that the degree centrality, betweenness centrality and RAPV indicators of stations can effectively identify the important stations that have a significant impact on the connectivity reliability of the network. In particular, the RAPV indicator effectively identifies stations that have the greatest influence on passenger travel realization. The connectivity reliability of Wuhan's subway network is sensitive to passenger tolerability coefficient, and reliability is greater during non-peak hours than during peak hours. In addition, the stations that are important to the connectivity reliability of the Wuhan subway have two features, i.e., they are located at the center of the city, and they are important for connecting subgraphs of the network.

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“…In addition to standard off-line TTPs, certain models are also used for real time (online) timetabling under disturbances, i.e., operational planning such as the models by Törnquist and Persson (2007), Törnquist (2012) or Quaglietta et al (2016). The final timetables can have a specific format, e.g., cyclic as in Zhang et al (2019b) or periodic as in Jamili et al (2012).…”

Section: Related Workmentioning

confidence: 99%

A disaggregate bundle method for train timetabling problems

Ali

Lindberg

Eliasson

et al. 2020

Journal of Rail Transport Planning & Management

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The train timetabling problem (TTP) consists of finding a feasible timetable for a number of trains which minimises some objective function, e.g., sum of running times or deviations from ideal departure times. One solution approach is to solve the dual problem of the TTP using so-called bundle methods. This paper presents a new bundle method that uses disaggregate data, as opposed to the standard bundle method which in a certain sense relies on aggregate data. We compare the disaggregate and aggregate methods on realistic train timetabling scenarios from the Iron Ore line in Northern Sweden. Numerical results indicate that the proposed disaggregate method reaches better solutions faster than the standard aggregate approach.

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Solving cyclic train timetabling problem through model reformulation: Extended time-space network construct and Alternating Direction Method of Multipliers methods

Cited by 81 publications

References 78 publications

A Fast Approach for Reoptimization of Railway Train Platforming in Case of Train Delays

A Fast Approach for Reoptimization of Railway Train Platforming in Case of Train Delays

Connectivity Reliability on an Urban Rail Transit Network from the Perspective of Passenger Travel

A disaggregate bundle method for train timetabling problems

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