IDEAS home Printed from https://ideas.repec.org/a/igg/jsir00/v4y2013i2p1-28.html
   My bibliography  Save this article

Contour Gradient Optimization

Author

Listed:
  • Zhou Wu

    (Department of Electrical and Electronic Engineering, City University of Hong Kong, Hong Kong)

  • Tommy W. S. Chow

    (Department of Electrical and Electronic Engineering, City University of Hong Kong, Hong Kong)

  • Shi Cheng

    (Division of Computer Science, The University of Nottingham Ningbo, Ningbo, China)

  • Yuhui Shi

    (Department of Electrical and Electronic Engineering, Xi'an Jiaotong-Liverpool University, Suzhou, China)

Abstract

Inspired by the local cooperation behavior in the real world, a new evolutionary algorithm Contour Gradient Optimization algorithm (CGO) is proposed for solving optimization problems. CGO is a new type of global search algorithm that emulates the cooperation among neighbors. Each individual in CGO evolves in its neighborhood environment to find a better region. Each individual moves with a velocity measured by the field of its nearest individuals. The field includes the attractive forces from its better neighbor in the higher contour level and the repulsive force from its worse neighbor in the lower contour level. Intensive simulations were performed and the results show that CGO is able to solve the tested multimodal optimization problems globally. In this paper, CGO is thoroughly compared with six different widely used optimization algorithms under sixteen different benchmark functions. The comparative analysis shows that CGO is comparatively better than these algorithms in the respect of accuracy and effectiveness.

Suggested Citation

  • Zhou Wu & Tommy W. S. Chow & Shi Cheng & Yuhui Shi, 2013. "Contour Gradient Optimization," International Journal of Swarm Intelligence Research (IJSIR), IGI Global, vol. 4(2), pages 1-28, April.
    • Handle: RePEc:igg:jsir00:v:4:y:2013:i:2:p:1-28
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/jsir.2013040101
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    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:igg:jsir00:v:4:y:2013:i:2:p:1-28. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.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.