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OeNB Project 18876

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OeNB Project Improving the performance of railway systems by using real-time algorithms in disruption management

Title:Improving the performance of railway systems by using real-time algorithms in disruption management
Funded byAnniversary Fund of the Oesterreichische Nationalbank (OeNB)
 
Project Number:18876
Project Start:1.11.2023
Contact:Vera.hemmelmayr@wu.ac.at
Abstract:

A well-functioning transport system is the backbone of economic activity. Disruptions due to extreme weather conditions or technical failures happen frequently and reduce the productivity of the railway system.  The economic costs of delays in passenger and freight transport are huge. Since it is mostly impossible to avoid disruptions, a fast and adequate response is necessary.

Currently, dispatchers at railway operators make these decisions mainly manually, based on experience and tacit knowledge. Advanced decision support that is part of the digital transformation of resource planning will lead to an increased productivity of the railway system. New technologies can provide the information necessary for automated planning support.

As a result of the disruption, the timetable, the rolling stock circulation plan and the crew schedule have to be changed by solving the underlying optimization problems. This project investigates the development of real-time optimization algorithms for rescheduling rolling stock and crew with the goal to optimize the use of railway infrastructure and increase the efficiency of railway operations.

We apply solution methods for combinatorial optimization problems. We study the use of exact and heuristic solution methods, and also a combination of these, so-called matheuristics. The exact methods provide lower bounds and solutions to small size instances so that we can evaluate the performance of the heuristics.

We will conduct a computational analysis of sequential, parallel and integrated approaches along solution quality and time so that recommendations for the type of optimization support of a railway operator can be found.

Project team:

  • Vera Hemmelmayr (Project leader)

  • Valentina Cacchiani

  • Roberto Maria Rosati

  • Manuel Schlenkrich

Recent activities:

  • Seminar on A Multi-Neighborhood Search Approach to Rolling Stock Rescheduling by Dr. Roberto Maria Rosati on 28 November 2024 (Bologna).

  • Rosati, R., Cacchiani, V., and Hemmelmayr, V. (2025). Models and algorithms for rolling stock re-scheduling. Working paper.

  • Rosati, R., Cacchiani, V., and Hemmelmayr, V. (2025). A Multi-Neighborhood Search Approach to Rolling Stock Rescheduling. Extended abstract accepted at   12th Triennial Symposium on Transportation Analysis conference (TRISTAN XII)

  • Schlenkrich, M., Cacchiani, V. and Hemmelmayr, V. (2025). Real-time crew rescheduling for disruption management in railway systems. Working paper.