IDEAS home Printed from
MyIDEAS: Log in (now much improved!) to save this paper

Solving a concrete sleepers production scheduling by genetic algorithms

Listed author(s):
Registered author(s):

    PRECON S.A is a manufacturing company dedicated to produce prefabricated concrete parts to several industries as rail transportation and agricultural industries.Recently, PRECON signed a contract with RENFE, the Spanish Nnational Rail Transportation Company to manufacture pre-stressed concrete sleepers for siding of the new railways of the high speed train AVE. The scheduling problem associated with the manufacturing process of the sleepers is very complex since it involves several constraints and objectives. The constraints are related with production capacity, the quantity of available moulds, satisfying demand and other operational constraints. The two main objectives are related with maximizing the usage of the manufacturing resources and minimizing the moulds movements. We developed a deterministic crowding genetic algorithm for this multiobjective problem. The algorithm has proved to be a powerful and flexible tool to solve the large-scale instance of this complex real scheduling problem.

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

    File URL:
    File Function: Whole Paper
    Download Restriction: no

    Paper provided by Department of Economics and Business, Universitat Pompeu Fabra in its series Economics Working Papers with number 736.

    in new window

    Date of creation: Jan 2004
    Handle: RePEc:upf:upfgen:736
    Contact details of provider: Web page:

    No references listed on IDEAS
    You can help add them by filling out this form.

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    When requesting a correction, please mention this item's handle: RePEc:upf:upfgen:736. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ()

    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 references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

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

    This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.