IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v348y2025i1d10.1007_s10479-022-05083-7.html
   My bibliography  Save this article

Survivability analysis and data simulation of logistic networks under different attacks

Author

Listed:
  • Hongyan Dui

    (Zhengzhou University)

  • Miao Cui

    (Zhengzhou University)

  • Junyong Tao

    (National University of Defense Technology)

  • Guanghan Bai

    (National University of Defense Technology)

Abstract

In recent years, the logistic network in combat tends to be complicated with the development of joint operations. When the network is attacked, how to effectively protect it and improve the survivability of the logistic network is vital for the overall performance of the combat system. In this study, the survivability of the logistic network against different attacks is analyzed. Three attack modes are considered, namely random attack, intentional attack, and comprehensive attack with partial information. Network efficiency and effective survival time are defined as the evaluation indexes of the network survivability. Then the importance measure and survivability analysis of the network are carried out. The impact of intentional and random attacks on network survivability in task redistribution mode is calculated. At last, a data simulation is given to demonstrate the proposed method.

Suggested Citation

  • Hongyan Dui & Miao Cui & Junyong Tao & Guanghan Bai, 2025. "Survivability analysis and data simulation of logistic networks under different attacks," Annals of Operations Research, Springer, vol. 348(1), pages 147-180, May.
    • Handle: RePEc:spr:annopr:v:348:y:2025:i:1:d:10.1007_s10479-022-05083-7
    DOI: 10.1007/s10479-022-05083-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-022-05083-7
    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/s10479-022-05083-7?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:spr:annopr:v:348:y:2025:i:1:d:10.1007_s10479-022-05083-7. 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.