IDEAS home Printed from https://ideas.repec.org/a/spr/joptap/v127y2005i2d10.1007_s10957-005-6553-6.html
   My bibliography  Save this article

New Inexact Line Search Method for Unconstrained Optimization

Author

Listed:
  • Z. J. Shi

    (Qufu Normal University
    Academy of Mathematics and Systems Science, Chinese Academy of Sciences)

  • J. Shen

    (University of Michigan)

Abstract

We propose a new inexact line search rule and analyze the global convergence and convergence rate of related descent methods. The new line search rule is similar to the Armijo line-search rule and contains it as a special case. We can choose a larger stepsize in each line-search procedure and maintain the global convergence of related line-search methods. This idea can make us design new line-search methods in some wider sense. In some special cases, the new descent method can reduce to the Barzilai and Borewein method. Numerical results show that the new line-search methods are efficient for solving unconstrained optimization problems.

Suggested Citation

  • Z. J. Shi & J. Shen, 2005. "New Inexact Line Search Method for Unconstrained Optimization," Journal of Optimization Theory and Applications, Springer, vol. 127(2), pages 425-446, November.
  • Handle: RePEc:spr:joptap:v:127:y:2005:i:2:d:10.1007_s10957-005-6553-6
    DOI: 10.1007/s10957-005-6553-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10957-005-6553-6
    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/s10957-005-6553-6?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.

    Citations

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


    Cited by:

    1. Antoine Soubeyran, 2023. "Variational rationality. Self regulation success as a succession of worthwhile moves that make sufficient progress," AMSE Working Papers 2307, Aix-Marseille School of Economics, France.
    2. Ping Hu & Xu-Qing Liu, 2013. "A Nonmonotone Line Search Slackness Technique for Unconstrained Optimization," Journal of Optimization Theory and Applications, Springer, vol. 158(3), pages 773-786, September.
    3. Zhiguang Zhang, 2010. "A New Method for Unconstrained Optimization Problem," Modern Applied Science, Canadian Center of Science and Education, vol. 4(10), pages 133-133, October.
    4. Shi, Zhenjun & Wang, Shengquan, 2011. "Nonmonotone adaptive trust region method," European Journal of Operational Research, Elsevier, vol. 208(1), pages 28-36, January.
    5. Vieira, Douglas Alexandre Gomes & Lisboa, Adriano Chaves, 2014. "Line search methods with guaranteed asymptotical convergence to an improving local optimum of multimodal functions," European Journal of Operational Research, Elsevier, vol. 235(1), pages 38-46.
    6. Zhang, Qiang & Liu, Jijun, 2024. "On fluorophore imaging by nonlinear diffusion model with dynamical iterative scheme," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 221(C), pages 533-549.
    7. Long, Jiancheng & Szeto, W.Y., 2019. "Congestion and environmental toll schemes for the morning commute with heterogeneous users and parallel routes," Transportation Research Part B: Methodological, Elsevier, vol. 129(C), pages 305-333.
    8. Sheng-Tong Zhou & Di Wang & Qian Xiao & Jian-min Zhou & Hong-Guang Li & Wen-Bing Tu, 2021. "An improved first order reliability method based on modified Armijo rule and interpolation-based backtracking scheme," Journal of Risk and Reliability, , vol. 235(2), pages 209-229, April.
    9. Antoine Soubeyran, 2022. "Variational rationality. Self regulation success as a succession of worthwhile moves that make sufficient progress," Working Papers hal-04041238, HAL.

    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:joptap:v:127:y:2005:i:2:d:10.1007_s10957-005-6553-6. 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.