Railway timetabling with integrated passenger distribution

Johann Hartleb*, Marie Schmidt

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

9 Citations (Scopus)
53 Downloads (Pure)


Timetabling for railway services often aims at optimizing travel times for passengers. At the same time, restricting assumptions on passenger behavior and passenger modeling are made. While research has shown that discrete choice models are suitable to estimate the distribution of passengers on routes, this has not been considered in timetabling yet. We investigate how to integrate a passenger distribution into an optimization framework for timetabling and present two mixed integer linear programs for this problem. Both approaches design timetables and simultaneously find a corresponding passenger distribution on available routes. One model uses a linear distribution model to estimate passenger route choices. The other model uses an integrated simulation framework to approximate a passenger distribution according to the logit model, a commonly used route choice model. We compare both new approaches with three state-of-the-art timetabling methods and a heuristic approach on a set of artificial instances and a partial network of Netherlands Railways (NS). Our experiments provide insights into the impact of considering multiple routes instead of a single route, and of integrated route choice versus predetermined route assignment with respect to the solution quality.

Original languageEnglish
Pages (from-to)953-966
Number of pages14
JournalEuropean Journal of Operational Research
Issue number3
Early online date19 Jun 2021
Publication statusPublished - 1 May 2022

Bibliographical note

Funding Information:
We thank Dennis Huisman from the Erasmus School of Economics at the Erasmus University Rotterdam and Netherlands Railways as well as Markus Friedrich from the Institute for Road and Transport Science at the University of Stuttgart for their valuable comments and suggestions throughout this work. We also thank two anonymous reviewers for their helpful remarks which greatly contributed to improving this paper.

Publisher Copyright:
© 2021 The Author(s)

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