An Optimization-Based Decision Support Tool for Incremental Train Timetabling

Oddvar Kloster (), Bjørnar Luteberget (), Carlo Mannino () and Giorgio Sartor ()
Additional contact information
Oddvar Kloster: SINTEF
Bjørnar Luteberget: SINTEF
Carlo Mannino: SINTEF
Giorgio Sartor: SINTEF

SN Operations Research Forum, 2023, vol. 4, issue 3, 1-20

Abstract: Abstract We consider the typical workflow of a route planner in the context of short-term train timetabling, that is, the incremental process of adjusting a timetable for the next day or up to the next year. This process usually alternates between (1) making rough modifications to an existing timetable (e.g., shifting the departure of a train by half an hour) and then (2) making small adjustments to regain feasibility (e.g., reduce or increase the dwell time of some trains in some stations). The most time-consuming element of this process is related to the second step, that is to manually eliminate all conflicts that may arise after a timetable has been modified. In this work, we propose a mixed-integer programming model tailored to solve precisely this problem, that is to find a conflict-free timetable that is as close as possible to a given one. Previous related work mostly focused on creating complex models to produce “optimal” timetables from scratch, which ultimately resulted in little to no practical applications. By using a simpler model, and by trusting route planners in steering the process towards a timetable with the desired qualities, we can get closer to handle real-life instances. The model has been integrated in a user interface that was tested and validated by Norwegian route planners to plan the yearly timetable of a busy railway line in Norway.

Keywords: Mixed-integer programming; Train timetabling; Job-shop scheduling (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s43069-023-00243-2

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