IDEAS home Printed from https://ideas.repec.org/a/eee/matcom/v43y1997i3p569-574.html
   My bibliography  Save this article

Prioritising and scheduling road projects by genetic algorithm

Author

Listed:
  • Qiu, Min

Abstract

The optimum timetable for implementing a set of road projects so as to achieve maximum investment effectiveness can be found by ranking or Goal Programming (GP) under the assumption that the payoffs of all the projects are divisible and proportional to their proportions undertaken. This assumption is valid for upgrading projects (Type 1) but not for new ones (Type 2). When this difference is taken into account, neither ranking nor GP are effective methods to find the optimum timetable. This paper develops a genetic algorithm (GA) to address this problem. The GA uses the ranking vector of the projects as a GA individual and then transforms it into a project proportion matrix by imposing the budget constraint. Experiments show that the GA can find the optimum solution with an acceptable accuracy, and when the projects are differentiated between Type 1 and 2, the GA finds the optimum timetable that is different from that in the case of all Type 1 projects.

Suggested Citation

  • Qiu, Min, 1997. "Prioritising and scheduling road projects by genetic algorithm," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 43(3), pages 569-574.
    • Handle: RePEc:eee:matcom:v:43:y:1997:i:3:p:569-574
    DOI: 10.1016/S0378-4754(97)82761-9
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378475497827619
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/S0378-4754(97)82761-9?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.

    Citations

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


    Cited by:

    1. John HE Taplin & Yuchao Sun, 2020. "Optimizing bus stop locations for walking access: Stops-first design of a feeder route to enhance a residential plan," Environment and Planning B, , vol. 47(7), pages 1237-1259, September.
    2. Khalifa Mohammed Al-Sobai & Shaligram Pokharel & Galal M. Abdella, 2020. "Perspectives on the Capabilities for the Selection of Strategic Projects," Sustainability, MDPI, vol. 12(19), pages 1-20, October.

    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:matcom:v:43:y:1997:i:3:p:569-574. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/mathematics-and-computers-in-simulation/ .

    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.