IDEAS home Printed from https://ideas.repec.org/a/etm/ijsrst/v12y2025i6id1398.html

Integrated Supply Chain–Finance Optimization Using Mixed Integer Programming: A Comprehensive Analysis

Author

Listed:
  • Samuel Oladapo Taiwo

Abstract

This study develops an integrated Mixed Integer Programming (MIP) framework for simultaneous optimization of supply chain design and financial performance. Unlike traditional models that decouple operational and financial decision-making, the proposed Integrated Supply Chain–Finance Optimization (ISFO) framework embeds Net Present Value (NPV), working capital constraints, and financial risk measures directly into strategic and tactical supply chain optimization. A multi-objective formulation enables structured analysis of profitability–risk trade-offs, while scenario-based stochastic programming captures demand, supply, and financial uncertainty. The results demonstrate that operational design decisions significantly alter liquidity exposure, capital structure, and long-term firm value. The study contributes a unified modeling architecture that enhances cross-functional integration between operations and finance, offering both theoretical advancement and practical decision-support relevance for industrial-scale supply chains.

Suggested Citation

  • Samuel Oladapo Taiwo, 2025. "Integrated Supply Chain–Finance Optimization Using Mixed Integer Programming: A Comprehensive Analysis," International Journal of Scientific Research in Science and Technology, Technoscience Academy, vol. 12(6), pages 784-804, December.
    • Handle: RePEc:etm:ijsrst:v12:y2025:i6:id:1398
    DOI: 10.32628/IJSRST25126503
    as

    Download full text from publisher

    File URL: https://ijsrst.com/home/article/view/IJSRST25126503
    File Function: Abstract page
    Download Restriction: no
    File URL: https://ijsrst.com/home/article/download/IJSRST25126503/IJSRST25126503
    File Function: Full text
    Download Restriction: no
    File URL: https://libkey.io/10.32628/IJSRST25126503?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
    ---><---

    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:etm:ijsrst:v12:y2025:i6:id:1398. 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: Pankaj Sharma (email available below). General contact details of provider: https://ijsrst.com/home .

    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.