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Optimal Train Dispatching by Benders’-Like Reformulation

Author

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  • Leonardo Lamorgese

    (SINTEF ICT, Oslo 0316, Norway)

  • Carlo Mannino

    (SINTEF ICT, Oslo 0316, Norway)

  • Mauro Piacentini

    (OptRail, Rome 00131, Italy)

Abstract

Train movements on railway lines are generally controlled by human dispatchers. Because disruptions often occur, dispatchers make real-time scheduling and routing decisions in an attempt to minimize deviations from the official timetable. This optimization problem is called train dispatching. We represent it as a mixed integer linear programming model, and solve it with a Benders’-like decomposition within a suitable master/slave scheme. Interestingly, the master and the slave problems correspond to a macroscopic and microscopic representation of the railway, recently exploited in heuristic approaches to the problem. The decomposition, along with some new modeling ideas, allowed us to solve real-life instances of practical interest to optimality. Automatic dispatching systems based on our macro/micro decomposition—in which both master and slave are solved heuristically—have been in operation in several Italian lines since 2011. The exact approach described in this paper outperforms such systems on our test bed of real-life instances. Furthermore, a system based on another version of the exact decomposition approach has been in operation since February 2014 on a line in Norway.

Suggested Citation

  • Leonardo Lamorgese & Carlo Mannino & Mauro Piacentini, 2016. "Optimal Train Dispatching by Benders’-Like Reformulation," Transportation Science, INFORMS, vol. 50(3), pages 910-925, August.
  • Handle: RePEc:inm:ortrsc:v:50:y:2016:i:3:p:910-925
    DOI: 10.1287/trsc.2015.0605
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    5. E. Ursavas & Stuart X. Zhu, 2018. "Integrated Passenger and Freight Train Planning on Shared-Use Corridors," Service Science, INFORMS, vol. 52(6), pages 1376-1390, December.
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    9. Rajnish Kumar & Goutam Sen & Samarjit Kar & Manoj Kumar Tiwari, 2018. "Station Dispatching Problem for a Large Terminal: A Constraint Programming Approach," Interfaces, INFORMS, vol. 48(6), pages 510-528, November.
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