IDEAS home Printed from https://ideas.repec.org/a/spr/mathme/v102y2025i1d10.1007_s00186-025-00904-4.html
   My bibliography  Save this article

An improved non-monotone trust region algorithm with a new adaptive radius for unconstrained optimization

Author

Listed:
  • Seyed Hamzeh Mirzaei

    (Semnan University)

  • Ali Ashrafi

    (Semnan University)

Abstract

In this study, we propose a trust region algorithm that inherits the remarkable properties of non-monotone strategy and adaptive radius. The radius of the algorithm is calculated based on a modified secant equation, using the values of the objective function and the gradient simultaneously in each iteration. The new non-monotone strategy is introduced to avoid the effect of monotonicity in slowing down the convergence speed, which leads to better practical and theoretical advantages than the previous non-monotone trust region algorithms. The global and superlinear convergence of the proposed algorithm are established under some standard conditions. Finally, the numerical experiments show the reduction of workload by the new algorithm and its efficiency.

Suggested Citation

  • Seyed Hamzeh Mirzaei & Ali Ashrafi, 2025. "An improved non-monotone trust region algorithm with a new adaptive radius for unconstrained optimization," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 102(1), pages 79-104, August.
    • Handle: RePEc:spr:mathme:v:102:y:2025:i:1:d:10.1007_s00186-025-00904-4
    DOI: 10.1007/s00186-025-00904-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00186-025-00904-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s00186-025-00904-4?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

    for a different version of it.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    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:spr:mathme:v:102:y:2025:i:1:d:10.1007_s00186-025-00904-4. 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.