IDEAS home Printed from https://ideas.repec.org/a/eee/transb/v32y1998i7p499-516.html
   My bibliography  Save this article

Expected shortest paths in dynamic and stochastic traffic networks

Author

Listed:
  • Fu, Liping
  • Rilett, L. R.

Abstract

The dynamic and stochastic shortest path problem (DSSPP) is defined as finding the expected shortest path in a traffic network where the link travel times are modeled as a continuous-time stochastic process. The objective of this paper is to examine the properties of the problem and to identify a technique that can be used to solve the DSSPP given information that will be available in networks with Intelligent Transportation System (ITS) capabilities. The paper first identifies a set of relationships between the mean and variance of the travel time of a given path and the mean and variance of the dynamic and stochastic link travel times on these networks. Based on these relationships it is shown that the DSSPP is computationally intractable and traditional shortest path algorithms cannot guarantee an optimal solution. A heuristic algorithm based on the k-shortest path algorithm is subsequently proposed to solve the problem. Lastly, the trade-off between solution quality and computational efficiency of the proposed algorithm is demonstrated on a realistic network from Edmonton, Alberta.

Suggested Citation

  • Fu, Liping & Rilett, L. R., 1998. "Expected shortest paths in dynamic and stochastic traffic networks," Transportation Research Part B: Methodological, Elsevier, vol. 32(7), pages 499-516, September.
    • Handle: RePEc:eee:transb:v:32:y:1998:i:7:p:499-516
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0191-2615(98)00016-2
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Stuart E. Dreyfus, 1969. "An Appraisal of Some Shortest-Path Algorithms," Operations Research, INFORMS, vol. 17(3), pages 395-412, June.
    2. Randolph W. Hall, 1986. "The Fastest Path through a Network with Random Time-Dependent Travel Times," Transportation Science, INFORMS, vol. 20(3), pages 182-188, August.
    3. Ishwar Murthy & Sumit Sarkar, 1996. "A Relaxation-Based Pruning Technique for a Class of Stochastic Shortest Path Problems," Transportation Science, INFORMS, vol. 30(3), pages 220-236, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Huang, He & Gao, Song, 2012. "Optimal paths in dynamic networks with dependent random link travel times," Transportation Research Part B: Methodological, Elsevier, vol. 46(5), pages 579-598.
    2. Fu, Liping, 2001. "An adaptive routing algorithm for in-vehicle route guidance systems with real-time information," Transportation Research Part B: Methodological, Elsevier, vol. 35(8), pages 749-765, September.
    3. Yang, Lixing & Zhang, Yan & Li, Shukai & Gao, Yuan, 2016. "A two-stage stochastic optimization model for the transfer activity choice in metro networks," Transportation Research Part B: Methodological, Elsevier, vol. 83(C), pages 271-297.
    4. Yueyue Fan & Yu Nie, 2006. "Optimal Routing for Maximizing the Travel Time Reliability," Networks and Spatial Economics, Springer, vol. 6(3), pages 333-344, September.
    5. Elise D. Miller-Hooks & Hani S. Mahmassani, 2000. "Least Expected Time Paths in Stochastic, Time-Varying Transportation Networks," Transportation Science, INFORMS, vol. 34(2), pages 198-215, May.
    6. Shahabi, Mehrdad & Unnikrishnan, Avinash & Boyles, Stephen D., 2013. "An outer approximation algorithm for the robust shortest path problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 58(C), pages 52-66.
    7. Ichoua, Soumia & Gendreau, Michel & Potvin, Jean-Yves, 2003. "Vehicle dispatching with time-dependent travel times," European Journal of Operational Research, Elsevier, vol. 144(2), pages 379-396, January.
    8. Opasanon, Sathaporn & Miller-Hooks, Elise, 2006. "Multicriteria adaptive paths in stochastic, time-varying networks," European Journal of Operational Research, Elsevier, vol. 173(1), pages 72-91, August.
    9. Antonio Polimeni & Antonino Vitetta, 2013. "Optimising Waiting at Nodes in Time-Dependent Networks: Cost Functions and Applications," Journal of Optimization Theory and Applications, Springer, vol. 156(3), pages 805-818, March.
    10. Axel Parmentier, 2019. "Algorithms for non-linear and stochastic resource constrained shortest path," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 89(2), pages 281-317, April.
    11. Levering, Nikki & Boon, Marko & Mandjes, Michel & Núñez-Queija, Rudesindo, 2022. "A framework for efficient dynamic routing under stochastically varying conditions," Transportation Research Part B: Methodological, Elsevier, vol. 160(C), pages 97-124.
    12. Redmond, Michael & Campbell, Ann Melissa & Ehmke, Jan Fabian, 2022. "Reliability in public transit networks considering backup itineraries," European Journal of Operational Research, Elsevier, vol. 300(3), pages 852-864.
    13. Nie, Yu (Marco) & Wu, Xing, 2009. "Shortest path problem considering on-time arrival probability," Transportation Research Part B: Methodological, Elsevier, vol. 43(6), pages 597-613, July.
    14. Yang, Baiyu & Miller-Hooks, Elise, 2004. "Adaptive routing considering delays due to signal operations," Transportation Research Part B: Methodological, Elsevier, vol. 38(5), pages 385-413, June.
    15. Raymond K. Cheung & B. Muralidharan, 2000. "Dynamic Routing for Priority Shipments in LTL Service Networks," Transportation Science, INFORMS, vol. 34(1), pages 86-98, February.
    16. Yang, Lixing & Zhou, Xuesong, 2017. "Optimizing on-time arrival probability and percentile travel time for elementary path finding in time-dependent transportation networks: Linear mixed integer programming reformulations," Transportation Research Part B: Methodological, Elsevier, vol. 96(C), pages 68-91.
    17. Miller-Hooks, Elise & Mahmassani, Hani, 2003. "Path comparisons for a priori and time-adaptive decisions in stochastic, time-varying networks," European Journal of Operational Research, Elsevier, vol. 146(1), pages 67-82, April.
    18. Rolando Quintero & Esteban Mendiola & Giovanni Guzmán & Miguel Torres-Ruiz & Carlos Guzmán Sánchez-Mejorada, 2023. "Algorithm for the Accelerated Calculation of Conceptual Distances in Large Knowledge Graphs," Mathematics, MDPI, vol. 11(23), pages 1-30, November.
    19. Pijls, Wim & Post, Henk, 2009. "A new bidirectional search algorithm with shortened postprocessing," European Journal of Operational Research, Elsevier, vol. 198(2), pages 363-369, October.
    20. Nielsen, Lars Relund & Andersen, Kim Allan & Pretolani, Daniele, 2006. "Bicriterion a priori route choice in stochastic time-dependent networks," CORAL Working Papers L-2006-10, University of Aarhus, Aarhus School of Business, Department of Business Studies.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transb:v:32:y:1998:i:7:p:499-516. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/548/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.