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Passenger-Based Intermodal Connection Optimization with Elastic Demands

Authors Boris Grimm , Ralf Borndörfer , Andrea Fraioli, Paula Franke , Giovanni Luca Giacco, Federico Marinucci, Tommaso Montino

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Subject Classification

ACM Subject Classification
  • Mathematics of computing → Combinatorial optimization
  • Mathematics of computing → Network optimization
  • Applied computing → Transportation
Keywords
  • Timetabling
  • Demand Elasticity
  • Discrete Choice
  • Mixed-Integer Nonlinear Programming
  • Heuristics

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Abstract

A railway network can attract additional passengers by improving the quality of service. One way to do that is to establish new train connections by slight shifts in arrival and departure times. We propose a connection optimization model to find a shifting of a given aperiodic timetable that maximizes the passenger volume, in which the demand is elastic and forecast by an integrated discrete choice logit model. The resulting large-scale mixed-integer non-linear non-convex programming problems can be solved by tailor-made heuristics for the entire Italian railway network with its 2,000 stations and 10,000 daily train trips, uncovering substantial potentials for connectivity improvements and boosts in demand.

Cite As Get BibTex

Boris Grimm, Ralf Borndörfer, Andrea Fraioli, Paula Franke, Giovanni Luca Giacco, Federico Marinucci, and Tommaso Montino. Passenger-Based Intermodal Connection Optimization with Elastic Demands. In 26th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2026). Open Access Series in Informatics (OASIcs), Volume 147, pp. 2:1-2:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026) https://doi.org/10.4230/OASIcs.ATMOS.2026.2

Author Details

Boris Grimm
  • Freie Universität Berlin, Germany
  • Zuse Institute Berlin, Germany
Ralf Borndörfer
  • Freie Universität Berlin, Germany
  • Zuse Institute Berlin, Germany
Andrea Fraioli
  • IVU Traffic Technologies Italia S.r.l., Rome, Italy
Paula Franke
  • Freie Universität Berlin, Germany
  • Zuse Institute Berlin, Germany
Giovanni Luca Giacco
  • Transport Data Management, Direzione Pianificazione Industriale, Trenitalia SpA, Rome, Italy
Federico Marinucci
  • IVU Traffic Technologies Italia S.r.l., Rome, Italy
Tommaso Montino
  • Transport Data Management, Direzione Pianificazione Industriale, Trenitalia SpA, Rome, Italy

Funding

The work for this article has been conducted in the MobilityLab of the Research Campus MODAL funded by the German Federal Ministry of Research, Technology and Space (BMFTR), fund number 05M25KEM. The work of authors 1, 2, and 4 is also supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy – The Berlin Mathematics Research Center MATH+ (EXC-2046/2, project ID: 390685689).

Acknowledgements

We thank three anonymous reviewers for their dedication and time to review this paper. Their fruitful comments improved our work.

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