IDEAS home Printed from https://ideas.repec.org/a/eee/transe/v200y2025ics136655452500184x.html
   My bibliography  Save this article

A three-stage matheuristic for the blood stochastic inventory routing problem

Author

Listed:
  • Yu, Vincent F.
  • Salsabila, Nabila Yuraisyah
  • Gunawan, Aldy
  • Siswanto, Nurhadi

Abstract

This research introduces a blood distribution system under vendor-managed inventory that considers uncertain supply and demand. We present it as the Blood Stochastic Inventory Routing Problem, formulating it as a two-stage stochastic programming model. To solve this problem, this study proposes a three-stage matheuristic that combines a perturbation heuristic, Adaptive Large Neighborhood Search, and an exact approach. From historical data of Surabaya Blood Center in Indonesia, six sets of new instances are generated under different settings. Computational results show that our proposed three-stage matheuristic outperforms CPLEX and a two-stage matheuristic by gaining optimal or better solutions within a significantly shorter computational time. Moreover, it is robust for solving large problems, as evidenced by its ability to find high-quality solutions within a reasonable time. Finally, managerial insights are derived by evaluating performance matrices under different uncertainty levels and scenarios. According to these insights, some practical strategies are suggested with respect to the decision-maker’s risk preferences and demand characteristics.

Suggested Citation

  • Yu, Vincent F. & Salsabila, Nabila Yuraisyah & Gunawan, Aldy & Siswanto, Nurhadi, 2025. "A three-stage matheuristic for the blood stochastic inventory routing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 200(C).
    • Handle: RePEc:eee:transe:v:200:y:2025:i:c:s136655452500184x
    DOI: 10.1016/j.tre.2025.104143
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S136655452500184X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tre.2025.104143?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:eee:transe:v:200:y:2025:i:c:s136655452500184x. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600244/description#description .

    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.