Scheduling and platforming trains at busy complex stations

Carey, Malachy; Carville, S.

doi:10.1016/s0965-8564(02)00012-5

Cited by 103 publications

(89 citation statements)

References 16 publications

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“…The average sub-objective values of different dispatching rules are illustrated in Figure 3. For the weighted number of delayed trains, rule 7 provides a much better solution than those of any other rules, and also we can see that the RS based on rule 7 is around 30% better than the one based on rule 8 (FIFO-EDD) that is commonly used in existing papers such as Carey (2003) [9]. For the platform track preference, rules 6 and 12 provide better solutions than those of any other rules.…”

Section: The Impact Of Dispatching Rules On Solutionsmentioning

confidence: 72%

“…Some researchers including Carey et al (2003) and Carey et al (2007) developed heuristics analogous to those successfully adopted by station dispatchers using manual methods [9,10]. Station dispatchers usually assign one train to one track at a time, and then a conflict check is conducted to avoid conflict between the train and all the previously assigned trains.…”

Section: Concept and Assumption Illustration In Our Tpp Versionmentioning

confidence: 99%

“…Station dispatchers usually assign one train to one track at a time, and then a conflict check is conducted to avoid conflict between the train and all the previously assigned trains. Although Carey et al (2003) and Carey et al (2007) experimented with different train orders such as random order, chronological order and reverse chronological order when choosing the next train to consider for scheduling in complex passenger stations, other orders are ruled out. In the station with relatively low density of train arrivals and departures and simple station layout, researchers such as Carey et al (2003) think that the train order (dispatching rule) when choosing the next train to consider for scheduling is not important, especially when heuristic methods are used to further optimize the solution based on a certain dispatching rule.…”

Section: Concept and Assumption Illustration In Our Tpp Versionmentioning

confidence: 99%

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An Experimental Analysis on Dispatching Rules for the Train Platforming Problem in Busy Complex Passenger Stations

Zeng

Zhang

Lei

2017

PROMET

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Section: The Impact Of Dispatching Rules On Solutionsmentioning

confidence: 72%

Section: Concept and Assumption Illustration In Our Tpp Versionmentioning

confidence: 99%

Section: Concept and Assumption Illustration In Our Tpp Versionmentioning

confidence: 99%

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An Experimental Analysis on Dispatching Rules for the Train Platforming Problem in Busy Complex Passenger Stations

Zeng

Zhang

Lei

2017

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“…Lübbecke and Zimmerman (2003b, p. 699) state that "the planning process can be covered only partly by a model". Alternatively, Carey and Carville (2003) developed an approach that mimics the behavior of a human planner. However, such an approach does not benefit from intelligent algorithmic support.…”

Section: Context Of the Problem Of Train Routingmentioning

confidence: 99%

k-Shortest routing of trains on shunting yards

Riezebos

Wezel

2008

OR Spectrum

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We consider the problem of designing algorithmic support for k-best routing decisions in train shunting scheduling. A study at the Netherlands Railways revealed that planners like to interact with the solution process of finding suitable routes. Two types of interaction were required: the possibility of assigning specific tracks to a route and of preventing the assignment of specific tracks to a route. The paper develops insights in the structure of the cost matrix in this k-best optimization problem. These dominance results are used in a two stage k-shortest path algorithm to support this task of the shunting planners. The solution approach determines the optimal sequence of the tracks that manually have been added to the route and determines the k shortest paths in this network. The approach is implemented in a prototype of a support system for shunting planners. The required calculation times for practical instances of the problem with varying numbers of alternative solutions (k ≤ 8) and intermediate tracks (m ≤ 5) are between 0.1 and 1.4 s. These calculation times are acceptable to provide adequate support to the planners of these shunting yards.Supported by the Netherlands Railways, Project "Rintel 4a". We gratefully acknowledge the management and planners of this company. Specifically, we would like to thank Dr. L.G. Kroon and the planners of location Zwolle for their willingness to co-operate.

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“…Extensive research has been carried out in the area of train timetabling problems [3][4][5], and train rescheduling research has recently attracted attention (as referred to in [6][7][8][9][10][11][12]). On the other hand, train stop deployment planning problems are reported only in passing in [13].…”

mentioning

confidence: 99%

A Train Stop Deployment Planning Algorithm Using a Petri-net-based Modelling Approach

Hirai¹,

Kunimatsu²,

Tomii

et al. 2009

QR of RTRI

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One of the essential roles of railway operators is to maintain punctual transportation services and safety (as referred to in [1,2]). The dispatcher in charge of train rescheduling in the train traffic control room must stop related trains immediately to ensure safety if an accident occurs on a railway line. On the other hand, particularly if an accident causes blockage of the line for a long time, the dispatcher must decide which trains should be running and which should be stopped. Moreover, the locations of the trains to be stopped should be decided appropriately at that point. This decision-making process is referred to as train stop deployment planning.A basic requirement in train stop deployment planning is to accommodate the train at a location with a platform. If a train stops before entering a station, the passengers on board cannot disembark to take alternative means of transport (such as buses or trains on other railway lines) to reach their destinations. It is therefore desirable to hold the train at a location with a platform.Another requirement is that a stopped train should not block following trains that are scheduled to run onto another line. If stopped trains occupy all tracks at a station, the following trains cannot pass through. If a following train has a destination on another line, the delay propagates to that line. To avoid such a scenario, train dispatchers must maintain routes for trains bound for other lines.A number of constraints exist in train stop deployment planning. A train must not be stopped at a station where the length of the platform is insufficient to accommodate it, as its rear end will extend onto the track. Onboard hardware such as signalling system units limits which tracks a train can enter.To prepare the deployment of train stops, these requirements and constraints must be considered. Simply moving trains to the nearest station can cause the problem of local trains blocking following express services.Extensive research has been carried out in the area of train timetabling problems [3][4][5], and train rescheduling research has recently attracted attention (as referred to in [6][7][8][9][10][11][12]). On the other hand, train stop deployment planning problems are reported only in passing in [13]. In that paper, the authors examined a problem on a line with only two train classes and a simple track layout. It is necessary to introduce sophisticated procedures for the professional treatment of today's complicated railway lines.In this study, we represented a train stop deployment planning problem as a Petri net model (referred to in [14,15]) and formalized it as an integer programming problem. Based on this modelling and formalization, we introduced an algorithm to solve the problem. The results of numerical experiments indicated that the algorithm is capable of finding a practical solution to the problem within a reasonable computing time.

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Scheduling and platforming trains at busy complex stations

Cited by 103 publications

References 16 publications

An Experimental Analysis on Dispatching Rules for the Train Platforming Problem in Busy Complex Passenger Stations

An Experimental Analysis on Dispatching Rules for the Train Platforming Problem in Busy Complex Passenger Stations

k-Shortest routing of trains on shunting yards

A Train Stop Deployment Planning Algorithm Using a Petri-net-based Modelling Approach

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