IDEAS home Printed from https://ideas.repec.org/a/hin/jnlaaa/940120.html
   My bibliography  Save this article

A New Method with Sufficient Descent Property for Unconstrained Optimization

Author

Listed:
  • Weiyi Qian
  • Haijuan Cui

Abstract

Recently, sufficient descent property plays an important role in the global convergence analysis of some iterative methods. In this paper, we propose a new iterative method for solving unconstrained optimization problems. This method provides a sufficient descent direction for objective function. Moreover, the global convergence of the proposed method is established under some appropriate conditions. We also report some numerical results and compare the performance of the proposed method with some existing methods. Numerical results indicate that the presented method is efficient.

Suggested Citation

  • Weiyi Qian & Haijuan Cui, 2014. "A New Method with Sufficient Descent Property for Unconstrained Optimization," Abstract and Applied Analysis, Hindawi, vol. 2014, pages 1-7, February.
    • Handle: RePEc:hin:jnlaaa:940120
    DOI: 10.1155/2014/940120
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/AAA/2014/940120.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/AAA/2014/940120.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2014/940120?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
    ---><---

    Citations

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


    Cited by:

    1. Siti Farhana Husin & Mustafa Mamat & Mohd Asrul Hery Ibrahim & Mohd Rivaie, 2020. "An Efficient Three-Term Iterative Method for Estimating Linear Approximation Models in Regression Analysis," Mathematics, MDPI, vol. 8(6), pages 1-12, June.

    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:hin:jnlaaa:940120. 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.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.