IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-1-4419-0820-9_32.html
   My bibliography  Save this book chapter

Reliability-based Dynamic Discrete Network Design with Stochastic Networks

In: Transportation and Traffic Theory 2009: Golden Jubilee

Author

Listed:
  • Hao Li

    (Delft University of Technology)

  • Michiel C.J. Bliemer

    (Delft University of Technology)

  • Piet H.L. Bovy

    (Delft University of Technology)

Abstract

Stochastic supply and fluctuating travel demand lead to stochastic travel times and travel costs for travelers. This paper will firstly focus on modeling of travelers’ departure time/route choice behavior under stochastic capacities. By analytically proving the equivalency of the scheduling approach and the mean variance approach, a generalized travel cost function is derived to model travelers’ departure time/route choice behavior under uncertainty. The proposed generalized travel cost function, which is more behaviorally sound and flexible, will be adopted to model a reliability-based long term user equilibrium with departure time choices. A reliability-based dynamic network design approach is proposed and formulated in which the numbers of lanes on all potential links are the design variables. A combined road network-oriented genetic algorithm and set evaluation algorithm is proposed to solve the dynamic network design problem. A new systematic approach is proposed to eliminate the infeasible, unrealistic and illogical lane designs in order to reduce the solution space and to save computation time. The proposed reliability-based dynamic network design approach is applied to a hypothetical network, and its solutions are compared to a corresponding static network design approach. It is concluded that the static network design approach may lead to poor designs. In general static traffic assignment underestimates the overall total network travel time and total network travel costs. The dynamic network design approach appears to result in a fairly good allocation of road capacity over space and makes the best utilization of the network capacity over time. A version of the Braess paradox appears in case of reliability-based cost functions in both static and dynamic networks.

Suggested Citation

  • Hao Li & Michiel C.J. Bliemer & Piet H.L. Bovy, 2009. "Reliability-based Dynamic Discrete Network Design with Stochastic Networks," Springer Books, in: William H. K. Lam & S. C. Wong & Hong K. Lo (ed.), Transportation and Traffic Theory 2009: Golden Jubilee, chapter 0, pages 651-673, Springer.
  • Handle: RePEc:spr:sprchp:978-1-4419-0820-9_32
    DOI: 10.1007/978-1-4419-0820-9_32
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Liu, Qiumin & Jiang, Rui & Liu, Ronghui & Zhao, Hui & Gao, Ziyou, 2020. "Travel cost budget based user equilibrium in a bottleneck model with stochastic capacity," Transportation Research Part B: Methodological, Elsevier, vol. 139(C), pages 1-37.
    2. Li, Hao & Tu, Huizhao & Hensher, David A., 2016. "Integrating the mean–variance and scheduling approaches to allow for schedule delay and trip time variability under uncertainty," Transportation Research Part A: Policy and Practice, Elsevier, vol. 89(C), pages 151-163.
    3. Biao Xiong & Bixin Li & Rong Fan & Qingzhong Zhou & Wu Li, 2017. "Modeling and Simulation for Effectiveness Evaluation of Dynamic Discrete Military Supply Chain Networks," Complexity, Hindawi, vol. 2017, pages 1-9, October.

    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:spr:sprchp:978-1-4419-0820-9_32. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.