Maintenance Appointments in Railway Rolling Stock Rescheduling

Wagenaar, Joris; Kroon, Leo; Schmidt, Marie

doi:10.1287/trsc.2016.0701

Cited by 28 publications

(10 citation statements)

References 18 publications

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“…Since the rolling stock scheduling problem is critical in the operational level of one railway company, it has attracted much attention for the last decades. Many researchers study this issue from a different point of view, e.g., Fioole et al [8]; Wagenaar et al [9]; Lusby et al [10]; Zhong et al [6]; and Cacchiani et al [11]. As a result, it is not difficult to find that most of the works related to rolling stock scheduling problems focus on conventional railways, where there are still some major differences from the rapid or urban rail transit.…”

Section: Literature Reviewmentioning

confidence: 99%

A Mixed Integer Linear Programming Model for Rolling Stock Deadhead Routing before the Operation Period in an Urban Rail Transit Line

Zhong

Zhang

Wang

et al. 2020

Journal of Advanced Transportation

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In an urban rail transit line, train services are performed by the rolling stocks that are initially stored at depots. Before the start of the operation period, rolling stocks consecutively leave the depots and run without passengers (deadhead routing) to the origin station of their corresponding first departure train service in an operation day (first train service) using either direct or indirect routes. This paper investigates the rolling stock deadhead routing problem in an urban transit line with multiple circulation plans, depots, and rolling stock types. Given the rolling stock circulation plans, the problem is to identify a deadhead route for the rolling stock required by the train services to cover the initial operation. By pregenerating all direct and indirect candidate deadhead routes in a polynomial manner, the problem is then nicely formulated as a mixed integer linear programming (MILP) model to minimize the total deadhead mileages. A real-world case from the urban rail transit line 3 of Chongqing in China is adopted to test the proposed method. Computational results demonstrate that the problems of large-scale instances can be quickly solved to optimality by commercial optimization solvers on a personal computer. In addition, our optimization method is better than the empirical practices in terms of the solution quality. Meanwhile, alternative measures can further decrease the total deadhead mileages according to the proposed model, e.g., opening idle switch stations and prolonging the time that is used for the rolling stock departure. Finally, the model is further extended to consider operating costs, and more computation cases are tested for better adapting to the practical operating conditions.

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Section: Literature Reviewmentioning

confidence: 99%

A Mixed Integer Linear Programming Model for Rolling Stock Deadhead Routing before the Operation Period in an Urban Rail Transit Line

Zhong

Zhang

Wang

et al. 2020

Journal of Advanced Transportation

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“…This implies that train units of the same type are considered interchangeable and that we have to be concerned only with the train unit types in a composition. We note that a similar strategy as developed by Wagenaar, Kroon, and Schmidt (2017) may be used to consider maintenance restrictions in our problem setting.…”

Section: Rolling Stock (Re)schedulingmentioning

confidence: 99%

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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“…Usually, a number of train units have a scheduled maintenance appointment during the day, and these appointments must be considered while rescheduling the rolling stock. proposed three mixed-integer programming models for this purpose [22].…”

Section: Disruption Management Of Train Units and Emusmentioning

confidence: 99%

High-Speed Railway EMUs’ Circulation Plan Optimization: A Two-Stage Optimization Algorithm Based on Column Generation

Wang

et al. 2020

IEEE Access

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Considering the characteristics of China's high-speed railway network and the allocation structure of Electric Multiple Units (EMUs), the EMUs operation management mode provides an effective technical route for EMUs route planning optimization. To reduce the number of EMUs, key factors such as the EMUs mileage, time limit, maintenance model, maintenance capability, night accommodation capacity, maintenance management mode, and train tasks are considered as constraints. The number of maintenance tasks is also the objective so that the EMUs route planning solution method is more integrated with actual production needs, and an optimization model of EMUs route planning is established to overcome the shortcomings of previous studies that did not sufficiently consider EMUs maintenance. To verify the feasibility and effectiveness of the proposed model and method of the proposed two-stage optimization algorithm based on column generation, a case study on the preparation of EMUs circulation planning for the Beijing-Shanghai high-speed railway network is conducted, and the results are analyzed. INDEX TERMS Branch and price algorithm, column generation, EMUs circulation plan, high-speed railway, two-stage optimization method.

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Maintenance Appointments in Railway Rolling Stock Rescheduling

Cited by 28 publications

References 18 publications

A Mixed Integer Linear Programming Model for Rolling Stock Deadhead Routing before the Operation Period in an Urban Rail Transit Line

A Mixed Integer Linear Programming Model for Rolling Stock Deadhead Routing before the Operation Period in an Urban Rail Transit Line

Reducing Passenger Delays by Rolling Stock Rescheduling

High-Speed Railway EMUs’ Circulation Plan Optimization: A Two-Stage Optimization Algorithm Based on Column Generation

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