IDEAS home Printed from https://ideas.repec.org/a/spr/coopap/v60y2015i2p513-544.html
   My bibliography  Save this article

Minimum penalty for constrained evolutionary optimization

Author

Listed:
  • Xiaosheng Li
  • Guoshan Zhang

Abstract

Penalty function methods are popular in dealing with the constrained optimization problems. How to choose reasonable penalty coefficients is a crucial problem which usually poses great influence on the quality of the final solution found. In this paper, the definition of the minimum penalty coefficient is proposed and the calculation formulas are established. Then a penalty coefficient value slightly larger than the minimum penalty coefficient is considered suitable. Furthermore, a Minimum Penalty algorithm (MP) is derived by combining the minimum penalty with a simple differential evolution. The presented method does not require parameter tuning. Experimental results on the 22 well-known benchmark test functions and 5 engineering design problems indicate that MP can achieve very competitive results compared with other state-of-the-art approaches. In addition, extra experiments are carried out to further verify the effectiveness of the proposed method for selecting proper penalty coefficients. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • Xiaosheng Li & Guoshan Zhang, 2015. "Minimum penalty for constrained evolutionary optimization," Computational Optimization and Applications, Springer, vol. 60(2), pages 513-544, March.
    • Handle: RePEc:spr:coopap:v:60:y:2015:i:2:p:513-544
    DOI: 10.1007/s10589-014-9676-6
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10589-014-9676-6
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10589-014-9676-6?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.

    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:spr:coopap:v:60:y:2015:i:2:p:513-544. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.