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Solving the multi-criteria time-dependent routing and scheduling problem in a multimodal fixed scheduled network

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  • Androutsopoulos, Konstantinos N.
  • Zografos, Konstantinos G.

Abstract

Multi-criteria routing and scheduling in a multimodal fixed scheduled network with time-dependent travel times involves the determination of the non-dominated itineraries (i.e., paths enhanced with scheduled departures) under the following constraints: (i) visiting a given set of intermediate stops in a specified sequence, and (ii) strict time windows on the origin, the destination and the intermediate stops. The objective of this paper is to present the formulation and algorithmic solution for the multi-criteria itinerary planning problem that takes into account the aforementioned features. The algorithmic approach proposed is based on the decomposition of the problem to a sequence of elementary itinerary sub-problems, solved by a dynamic programming algorithm. The computational performance of the algorithms on a set of large scale test problems indicates non-prohibitive time requirements and encourages its integration into travel planning decision support systems.

Suggested Citation

  • Androutsopoulos, Konstantinos N. & Zografos, Konstantinos G., 2009. "Solving the multi-criteria time-dependent routing and scheduling problem in a multimodal fixed scheduled network," European Journal of Operational Research, Elsevier, vol. 192(1), pages 18-28, January.
    • Handle: RePEc:eee:ejores:v:192:y:2009:i:1:p:18-28
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    Cited by:

    1. Zweers, Bernard G. & van der Mei, Rob D., 2022. "Minimum costs paths in intermodal transportation networks with stochastic travel times and overbookings," European Journal of Operational Research, Elsevier, vol. 300(1), pages 178-188.
    2. Zhang, Yu & Tang, Jiafu, 2018. "A robust optimization approach for itinerary planning with deadline," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 113(C), pages 56-74.
    3. Gecchelin, Tommaso & Webb, Jeremy, 2019. "Modular dynamic ride-sharing transport systems," Economic Analysis and Policy, Elsevier, vol. 61(C), pages 111-117.
    4. Andrew Ensor & Felipe Lillo, 2016. "Colored-Edge Graph Approach for the Modeling of Multimodal Transportation Systems," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 33(01), pages 1-21, February.
    5. Said Dabia & Stefan Ropke & Tom van Woensel & Ton De Kok, 2013. "Branch and Price for the Time-Dependent Vehicle Routing Problem with Time Windows," Transportation Science, INFORMS, vol. 47(3), pages 380-396, August.
    6. Zhang, Yu & Tang, Jiafu, 2018. "Itinerary planning with time budget for risk-averse travelers," European Journal of Operational Research, Elsevier, vol. 267(1), pages 288-303.
    7. Zajac, Sandra & Huber, Sandra, 2021. "Objectives and methods in multi-objective routing problems: a survey and classification scheme," European Journal of Operational Research, Elsevier, vol. 290(1), pages 1-25.
    8. Cats, Oded & Koutsopoulos, Haris N. & Burghout, Wilco & Toledo, Tomer, 2013. "Effect of real-time transit information on dynamic path choice of passengers," Working papers in Transport Economics 2013:28, CTS - Centre for Transport Studies Stockholm (KTH and VTI).
    9. Häme, Lauri & Hakula, Harri, 2013. "Dynamic journeying under uncertainty," European Journal of Operational Research, Elsevier, vol. 225(3), pages 455-471.

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