Advanced Search
MyIDEAS: Login to save this article or follow this journal

A genetic algorithms simulation approach for the multi-attribute combinatorial dispatching decision problem


Author Info

  • Yang, Taho
  • Kuo, Yiyo
  • Cho, Chiwoon
Registered author(s):


    No abstract is available for this item.

    Download Info

    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:
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

    Bibliographic Info

    Article provided by Elsevier in its journal European Journal of Operational Research.

    Volume (Year): 176 (2007)
    Issue (Month): 3 (February)
    Pages: 1859-1873

    as in new window
    Handle: RePEc:eee:ejores:v:176:y:2007:i:3:p:1859-1873

    Contact details of provider:
    Web page:

    Related research



    References listed on IDEAS
    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
    as in new window
    1. Rajendran, Chandrasekharan & Holthaus, Oliver, 1999. "A comparative study of dispatching rules in dynamic flowshops and jobshops," European Journal of Operational Research, Elsevier, vol. 116(1), pages 156-170, July.
    2. Pongcharoen, P. & Hicks, C. & Braiden, P. M. & Stewardson, D. J., 2002. "Determining optimum Genetic Algorithm parameters for scheduling the manufacturing and assembly of complex products," International Journal of Production Economics, Elsevier, vol. 78(3), pages 311-322, August.
    3. Botta-Genoulaz, Valerie, 2000. "Hybrid flow shop scheduling with precedence constraints and time lags to minimize maximum lateness," International Journal of Production Economics, Elsevier, vol. 64(1-3), pages 101-111, March.
    4. Sarper, H. & Henry, M. C., 1996. "Combinatorial evaluation of six dispatching rules in a dynamic two-machine flow shop," Omega, Elsevier, vol. 24(1), pages 73-81, February.
    5. Azadivar, Farhad & Tompkins, George, 1999. "Simulation optimization with qualitative variables and structural model changes: A genetic algorithm approach," European Journal of Operational Research, Elsevier, vol. 113(1), pages 169-182, February.
    6. Petroni, Alberto & Rizzi, Antonio, 2002. "A fuzzy logic based methodology to rank shop floor dispatching rules," International Journal of Production Economics, Elsevier, vol. 76(1), pages 99-108, March.
    7. P. Pongcharoen & D. J. Stewardson & C. Hicks & P. M. Braiden, 2001. "Applying designed experiments to optimize the performance of genetic algorithms used for scheduling complex products in the capital goods industry," Journal of Applied Statistics, Taylor & Francis Journals, vol. 28(3-4), pages 441-455.
    Full references (including those not matched with items on IDEAS)


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

    Cited by:
    1. Pickardt, Christoph W. & Hildebrandt, Torsten & Branke, J├╝rgen & Heger, Jens & Scholz-Reiter, Bernd, 2013. "Evolutionary generation of dispatching rule sets for complex dynamic scheduling problems," International Journal of Production Economics, Elsevier, vol. 145(1), pages 67-77.
    2. Chiang, Tsung-Che & Fu, Li-Chen, 2009. "Using a family of critical ratio-based approaches to minimize the number of tardy jobs in the job shop with sequence dependent setup times," European Journal of Operational Research, Elsevier, vol. 196(1), pages 78-92, July.
    3. Branke, Juergen & Pickardt, Christoph W., 2011. "Evolutionary search for difficult problem instances to support the design of job shop dispatching rules," European Journal of Operational Research, Elsevier, vol. 212(1), pages 22-32, July.


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


    Access and download statistics


    When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:176:y:2007:i:3:p:1859-1873. 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: (Zhang, Lei).

    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.