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An adaptive routing approach for personal rapid transit

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  • Kaspar Schüpbach
  • Rico Zenklusen

Abstract

Personal Rapid Transit (PRT) is a public transportation mode, in which small automated vehicles transport passengers on demand. Central control of the vehicles leads to interesting possibilities for optimized routings. The complexity of the involved routing problems together with the fact that routing algorithms for PRT essentially have to run in real-time often leads to the choice of fast greedy approaches. The most common routing approach is arguably a sequential one, where upcoming requests are greedily served in a quickest way without interfering with previously routed vehicles. The simplicity of this approach stems from the fact that a chosen route is never changed later. This is as well the main drawback of it, potentially leading to large detours. It is natural to ask how much one could gain by using a more adaptive routing strategy. This question is the main motivation of this article. In this paper, we first suggest a simple mathematical model for PRT, and then introduce a new adaptive routing algorithm that repeatedly uses solutions to an LP as a guide to route vehicles. Our routing approach incorporates new requests in the LP as soon as they appear, and reoptimizes the routing of all currently used vehicles, contrary to sequential routing. We provide preliminary computational results that give first evidence of the potential gains of an adaptive routing strategy, as used in our algorithm. Copyright Springer-Verlag 2013

Suggested Citation

  • Kaspar Schüpbach & Rico Zenklusen, 2013. "An adaptive routing approach for personal rapid transit," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 77(3), pages 371-380, June.
    • Handle: RePEc:spr:mathme:v:77:y:2013:i:3:p:371-380
    DOI: 10.1007/s00186-012-0403-8
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    References listed on IDEAS

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    1. Nirup N. Krishnamurthy & Rajan Batta & Mark H. Karwan, 1993. "Developing Conflict-Free Routes for Automated Guided Vehicles," Operations Research, INFORMS, vol. 41(6), pages 1077-1090, December.
    2. L. R. Ford & D. R. Fulkerson, 1958. "Constructing Maximal Dynamic Flows from Static Flows," Operations Research, INFORMS, vol. 6(3), pages 419-433, June.
    3. John D. Lees-Miller & R. Eddie Wilson, 2011. "Proactive empty vehicle redistribution for personal rapid transit and taxis," Transportation Planning and Technology, Taylor & Francis Journals, vol. 35(1), pages 17-30, September.
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