IDEAS home Printed from https://ideas.repec.org/a/spr/flsman/v37y2025i4d10.1007_s10696-024-09531-3.html
   My bibliography  Save this article

A Benders decomposition approach for planning home blood donations

Author

Listed:
  • Tiziano Bacci

    (Consiglio Nazionale delle Ricerche, Istituto di Analisi dei Sistemi ed Informatica “Antonio Ruberti”)

  • Ettore Lanzarone

    (University of Bergamo, Department of Management, Information and Production Engineering)

  • Sara Mattia

    (Consiglio Nazionale delle Ricerche, Istituto di Analisi dei Sistemi ed Informatica “Antonio Ruberti”)

  • Paolo Ventura

    (Consiglio Nazionale delle Ricerche, Istituto di Analisi dei Sistemi ed Informatica “Antonio Ruberti”)

Abstract

Blood donations are crucial for the health system. We consider the problem of planning blood donation services, where the donors are reached at home. The scope is to minimize the penalty for the unserved donors, while guaranteeing that the available resources for implementing the service are not exceeded and that the appointment preferences of the donors are met. We present an offline model for this setting, where the produced solution must be robust with respect to the availability of the donors, which is not known in advance and is managed in a stochastic way using scenarios. A Benders decomposition approach to solve this model is developed. The proposed algorithm is tested on real-life instances coming from the Milan department of the Associazione Volontari Italiani Sangue (AVIS).

Suggested Citation

  • Tiziano Bacci & Ettore Lanzarone & Sara Mattia & Paolo Ventura, 2025. "A Benders decomposition approach for planning home blood donations," Flexible Services and Manufacturing Journal, Springer, vol. 37(4), pages 1117-1147, December.
    • Handle: RePEc:spr:flsman:v:37:y:2025:i:4:d:10.1007_s10696-024-09531-3
    DOI: 10.1007/s10696-024-09531-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10696-024-09531-3
    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/s10696-024-09531-3?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:flsman:v:37:y:2025:i:4:d:10.1007_s10696-024-09531-3. 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.