IDEAS home Printed from https://ideas.repec.org/a/wsi/apjorx/v30y2013i03ns0217595913400058.html
   My bibliography  Save this article

An Adaptive Gradient Algorithm For Large-Scale Nonlinear Bound Constrained Optimization

Author

Listed:
  • WANYOU CHENG

    (College of Computer, Dongguan University of Technology, Dongguan 523000, China)

  • ERBAO CAO

    (College of Econometrics and Trade, Hunan University, Changsha 410082, China)

Abstract

In this paper, an adaptive gradient algorithm (AGM) for box constrained optimization is developed. The algorithm is based on an active set identification technique and consists of a nonmonotone gradient projection step, a conjugate gradient step and a rule for branching between the two steps. We show that the method is globally convergent under appropriate conditions. Numerical experiments are presented using bound constrained problems in the CUTEr test problem library.

Suggested Citation

  • Wanyou Cheng & Erbao Cao, 2013. "An Adaptive Gradient Algorithm For Large-Scale Nonlinear Bound Constrained Optimization," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 30(03), pages 1-12.
    • Handle: RePEc:wsi:apjorx:v:30:y:2013:i:03:n:s0217595913400058
    DOI: 10.1142/S0217595913400058
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S0217595913400058
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://libkey.io/10.1142/S0217595913400058?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:wsi:apjorx:v:30:y:2013:i:03:n:s0217595913400058. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/apjor/apjor.shtml .

    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.