IDEAS home Printed from https://ideas.repec.org/a/ids/ijisen/v6y2010i4p417-440.html
   My bibliography  Save this article

A multi-objective genetic algorithm for scheduling optimisation of m job families on a single machine

Author

Listed:
  • Ali Azadeh
  • Abbas Keramati
  • Afshin Karimi
  • Mohsen Moghaddam

Abstract

This paper presents multi-objective scheduling of m job families on a single machine by multi-objective genetic algorithm (MOGA). We follow optimisation in three objectives: improving the tardiness, increasing the machine utilisation and decreasing the cycle time. MOGA is the combination of genetic algorithm with multi-criteria decision making. Moreover, N jobs are placed for m job families. Each job has three main distinct features including arrival time, time of processing and due date. Also, we consider setup time for each job and sequence-dependent setup time for changing jobs in different families. In order to determine the superiority of MOGA solution, we compared it with shortest processing time and earliest due date solutions. The improvement of MOGA over other approaches is shown by different cases.

Suggested Citation

  • Ali Azadeh & Abbas Keramati & Afshin Karimi & Mohsen Moghaddam, 2010. "A multi-objective genetic algorithm for scheduling optimisation of m job families on a single machine," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 6(4), pages 417-440.
    • Handle: RePEc:ids:ijisen:v:6:y:2010:i:4:p:417-440
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=35724
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

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

    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:ids:ijisen:v:6:y:2010:i:4:p:417-440. 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=188 .

    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.