IDEAS home Printed from https://ideas.repec.org/a/ids/ijores/v16y2013i1p81-95.html
   My bibliography  Save this article

Vector optimisation using fuzzy preference in evolutionary strategy based firefly algorithm

Author

Listed:
  • Surafel Luleseged Tilahun
  • Hong Choon Ong

Abstract

Solving vector optimisation entails the conflict among component objectives. The best solution depends on the preference of the decision-maker. Firefly algorithm is one of the recently proposed metaheuristic algorithms for optimisation problems. In this paper, the random movement of the brighter firefly is modified by using (1 + 1)-evolutionary strategy to identify the direction in which the brightness increases. We also show how to generate a dynamic weight for each component of the vector by using a fuzzy trade-off preference. This dynamic weight will be imbedded in computing the intensity of light of fireflies in the algorithm. From the simulation results, it is shown that using fuzzy preference is promising to obtain solutions according to the given fuzzy preference. Furthermore, simulation results show that the evolutionary strategy based firefly algorithm performs better than the ordinary firefly algorithm.

Suggested Citation

  • Surafel Luleseged Tilahun & Hong Choon Ong, 2013. "Vector optimisation using fuzzy preference in evolutionary strategy based firefly algorithm," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 16(1), pages 81-95.
    • Handle: RePEc:ids:ijores:v:16:y:2013:i:1:p:81-95
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=50541
    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.

    Citations

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


    Cited by:

    1. Surafel Luleseged Tilahun & Hong Choon Ong, 2015. "Prey-Predator Algorithm: A New Metaheuristic Algorithm for Optimization Problems," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 14(06), pages 1331-1352, November.

    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:ijores:v:16:y:2013:i:1:p:81-95. 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=170 .

    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.