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Improving Vehicle Scheduling Support by Efficient Algorithms

  • Taïeb Mellouli
Conference paper
Part of the Operations Research Proceedings book series (ORP, volume 1996)

Abstract

In this paper, the minimum fleet size problem is investigated: Find the minimum number of vehicles to serve a set of trips of a given timetable for a transportation system. First, we present an algorithm for the basic problem requiring only linear-time after suitably sorting input data. This improves a quadratic-time greedy algorithm developed in [Su95]. Our algorithm was implemented and tested with real-life data indicating a good performance. Generated diagrams on vehicle standing times are shown to be useful for various tasks. Second, Min-Max-results for the minimum fleet size problem are discussed. We argue that Dilworth’s chain decomposition theorem works only if unrestricted deadheading, i.e., adding non-profit ‘empty’ trips, is permitted and thus its application to the case of railway or airline passenger traffic is misleading. To remedy this lack, we consider a particular network flow model for the no deadheading case, formulate a Min-Max-result, and discuss its implications- along with efficient algorithms-for vehicle as well as trip and deadhead trip scheduling.

Keywords

Greedy Algorithm Terminal Station Minimum Flow Greedy Approach Vehicle Schedule 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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    Ahuja, R.K., Magnanti, T.L., and Orlin, J.B., L.: Network Flows. Prentice Hall, NJ, 1993.Google Scholar
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    Bartlett, T.E.: “An algorithm for the minimum number of transport units to maintain a fixed schedule” Bartlett, T.E. and Charnes, A.: “Part II: Generalizations and Analysis”. Nav. Res. Log.Q., 4,139–149 and 207–220, 1957.CrossRefGoogle Scholar
  3. [FoFu62]
    Ford, L.R. and Fulkerson, D.R.: Flows in Networks. Princeton U.P., Princeton, NJ, 1962.Google Scholar
  4. [MeSu96]
    Mellouli, T. and Suhl, L.: “Supporting Planning and Operation Time Control in Transportation Systems”. Symposium on Operations Research (SOR’96). Braunschweig, Germany, 1996.Google Scholar
  5. [Su95]
    Suhl, L.: Computer-Aided Scheduling: An Airline Perspective. Gabler - DUV, Wiesbaden, 1995.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Taïeb Mellouli
    • 1
  1. 1.Dept. of Business Computing Decision Support & OR LaboratoryUniversity of PaderbornGermany

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