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Public Transport

, Volume 11, Issue 1, pp 1–25 | Cite as

Delay and disruption management in local public transportation via real-time vehicle and crew re-scheduling: a case study

  • Federico Malucelli
  • Emanuele TresoldiEmail author
Case Study and Application
  • 182 Downloads

Abstract

Local public transport companies, especially in large cities, are facing every day the problem of managing delays and small disruptions. Disruption management is a well-established practice in airlines and railways. However, in local public transport the approaches to these problems have followed a different path, mainly focusing on holding and short-turning strategies not directly associated with the driver scheduling. In this paper we consider the case of the management of urban surface lines of Azienda Trasporti Milanese (ATM) of Milan. The main issues are the service regularity as a measure of the quality of service, and the minimization of the operational costs due to changes in the planned driver scheduling. We propose a simulation-based optimization system to cope with delays and small disruptions that can be effectively used in a real-time environment and takes into account both vehicle and driver scheduling. The proposed approach is tested on real data to prove its actual applicability.

Keywords

Delay management Disruption management Local public transportation Real-time optimization Real-word scenario Big data Vehicle scheduling Crew scheduling 

Notes

Acknowledgements

We would like to tank Stefano Gualandi, Fabrizio Ronchi and Stefano Scotti for their contribution that greatly improved the quality and completeness of this paper. MAIOR s.r.l. had a fundamental role in the analysis of the problem and in defining the data retrieval tools. We are gratefully indebted with the reviewers for their constructive comments and helpful suggestions. This work has been awarded the “Best OR application 2016”, by the Italian Association of Operations Research (AIRO).

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Dipartimento di Elettronica, Informazione e BioingegneriaPolitecnico di MilanoMilanItaly
  2. 2.Dipartimento di InformaticaUniversità degli Studi di MilanoMilanItaly

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