IDEAS home Printed from https://ideas.repec.org/a/taf/transp/v31y2008i2p135-152.html
   My bibliography  Save this article

Mitigating Traffic Congestion: Solving the Ride-Matching Problem by Bee Colony Optimization

Author

Listed:
  • Dušan Teodorović
  • Mauro Dell’ Orco

Abstract

Urban road networks in many countries are severely congested. Expanding traffic network capacities by building more roads is very costly as well as environmentally damaging. Researchers, planners, and transportation professionals have developed various Travel Demand Management (TDM) techniques, i.e. strategies that increase travel choices to travelers. Ride sharing is one of the widely used TDM techniques that assumes the participation of two or more persons that together share a vehicle when traveling from few origins to few destinations. In ride-matching systems, commuters wishing to participate in ride sharing are matched by where they live and work, and by their work schedule. There is no standard method in the open literature to determine the best ride-matching method. In this paper, an attempt has been made to develop the methodology capable to solve the ride-matching problem. The proposed Bee Colony Optimization Metaheuristic is sufficiently general and could be applied to various combinatorial optimization problems.

Suggested Citation

  • Dušan Teodorović & Mauro Dell’ Orco, 2008. "Mitigating Traffic Congestion: Solving the Ride-Matching Problem by Bee Colony Optimization," Transportation Planning and Technology, Taylor & Francis Journals, vol. 31(2), pages 135-152, January.
  • Handle: RePEc:taf:transp:v:31:y:2008:i:2:p:135-152
    DOI: 10.1080/03081060801948027
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/03081060801948027
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/03081060801948027?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

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

    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:taf:transp:v:31:y:2008:i:2:p:135-152. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/GTPT20 .

    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.