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Critical Review of Time-Dependent Shortest Path Algorithms: A Multimodal Trip Planner Perspective

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  • Bradley Casey
  • Ashish Bhaskar
  • Hao Guo
  • Edward Chung

Abstract

A multimodal trip planner that produces optimal journeys involving both public transport and private vehicle legs has to solve a number of shortest path problems, both on the road network and the public transport network. The algorithms that are used to solve these shortest path problems have been researched since the late 1950s. However, in order to provide accurate journey plans that can be trusted by the user, the variability of travel times caused by traffic congestion must be taken into consideration. This requires the use of more sophisticated time-dependent shortest path algorithms, which have only been researched in depth over the last two decades, from the mid-1990s. This paper will review and compare nine algorithms that have been proposed in the literature, discussing the advantages and disadvantages of each algorithm on the basis of five important criteria that must be considered when choosing one or more of them to implement in a multimodal trip planner.

Suggested Citation

  • Bradley Casey & Ashish Bhaskar & Hao Guo & Edward Chung, 2014. "Critical Review of Time-Dependent Shortest Path Algorithms: A Multimodal Trip Planner Perspective," Transport Reviews, Taylor & Francis Journals, vol. 34(4), pages 522-539, July.
    • Handle: RePEc:taf:transr:v:34:y:2014:i:4:p:522-539
    DOI: 10.1080/01441647.2014.921797
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    References listed on IDEAS

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    1. Daniel Delling & Giacomo Nannicini, 2012. "Core Routing on Dynamic Time-Dependent Road Networks," INFORMS Journal on Computing, INFORMS, vol. 24(2), pages 187-201, May.
    2. Stuart E. Dreyfus, 1969. "An Appraisal of Some Shortest-Path Algorithms," Operations Research, INFORMS, vol. 17(3), pages 395-412, June.
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    Cited by:

    1. Panagiotis Georgakis & Adel Almohammad & Efthimios Bothos & Babis Magoutas & Kostantina Arnaoutaki & Gregoris Mentzas, 2020. "Heuristic-Based Journey Planner for Mobility as a Service (MaaS)," Sustainability, MDPI, vol. 12(23), pages 1-25, December.
    2. Zhaoxia Guo & Stein W. Wallace & Michal Kaut, 2019. "Vehicle Routing with Space- and Time-Correlated Stochastic Travel Times: Evaluating the Objective Function," INFORMS Journal on Computing, INFORMS, vol. 31(4), pages 654-670, October.
    3. López, David & Lozano, Angélica, 2020. "Shortest hyperpaths in a multimodal hypergraph with real-time information on some transit lines," Transportation Research Part A: Policy and Practice, Elsevier, vol. 137(C), pages 541-559.
    4. Nir Halman & Mikhail Y. Kovalyov & Alain Quilliot & Dvir Shabtay & Moshe Zofi, 2019. "Bi-criteria path problem with minimum length and maximum survival probability," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 41(2), pages 469-489, June.

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