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Managing and Preventing Delays in Railway Traffic by Simulation and Optimization

  • Leena Suhl
  • Taïeb Mellouli
  • Claus Biederbick
  • Johannes Goecke
Part of the Applied Optimization book series (APOP, volume 48)

Abstract

When a disturbance occurs within a railway network, a dispatcher has to decide ‘online’ about changes in the schedule in order to reduce induced delays and disadvantages for passengers. Computer assistance for dispatchers is needed. In an earlier work, a system architecture for a decision support system for operations control is proposed. This paper concerns the simulation part of this system, needed to manage and prevent delays. Besides operations control, we stress the usefulness of simulation already in the planning phase to prevent delays at operations. Analyzing (types of) disturbances, suitable distributions of delays are generated, and simulation is used to test the robustness of the timetable against disturbances. As a test vehicle, a computer-based environment configured for German Rail’s network has been developed. Robustness depends on dimensions of conflicts and of passengers involved. Conflicts and their causes directly depend on the ‘waiting time rules’ in use. By a simulation study, the quality of these rules can be evaluated and corrected. Preventing delays may be achieved by a better planning, too. Special optimization models can be used to increase buffer times without need of extra resources.

Keywords

operations control railways preventing delays simulation optimization 

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References

  1. Bacceli, F., Cohen, G., Olsder, GJ., and Quadrat, J.P. (1992). Synchronization and linearity — An algebra for discrete event systems. John Wiley Sons, Chichester.Google Scholar
  2. Egmond, R.-J. van. Propagation of delays in public transport. Presented at the 6th Meeting of the EURO Working Group on Transportation. September 9–11, 1998. Gothenburg.Google Scholar
  3. Goecke, J. (1996). Entwicklung eines graphisch-interaktiven Systems zur Unterstützung der netzweiten Konfliktlösung bei Zugverspätungen der Deutschen Bahn AG. Diploma thesis. Decision Support OR Lab. University of Paderborn.Google Scholar
  4. Manivannan, M.S. (1998). Simulation of Logistics and Transportation Systems. In Handbook of Simulation — Principles, Methodology, Advances, Applications, and Practice (Banks J.), pp. 571–604. Wiley. New York.Google Scholar
  5. Mellouli, T. (1998). Periodic Maintenance Routing of German Rail’s IC/EC Trains by a Flow Model based on a State-Expanded Time-Space Network. Presented at the 6th Meeting of the EURO Working Group on Transportation. September 9–11, 1998. Gothenburg.Google Scholar
  6. Stelbrink, M. (1998). Konzeption und prototypische Implementierung eines verteilten, echtzeitbasierten Kundeninformationssystems bei der Deutschen Bahn AG unter Verwendung von Intranet-Technologie. Diploma thesis. Decision Support OR Lab. University of Paderborn.Google Scholar
  7. Suhl, L. and Mellouli, T. (1999). Requirements for, and Design of, an Operations Control System for Railways. In Computer-Aided Transit Scheduling (Wilson N.H.M.), LNEMS, Vol. 471, pp. 371–390. Springer. Berlin — Heidelberg.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2001

Authors and Affiliations

  • Leena Suhl
    • 1
  • Taïeb Mellouli
    • 1
  • Claus Biederbick
    • 1
  • Johannes Goecke
    • 1
  1. 1.Decision Support & OR Laboratory, Department of Business ComputingUniversity of PaderbornPaderbornGermany

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