IDEAS home Printed from https://ideas.repec.org/a/jbh/ijsrcs/v11y2025i2id1381.html

AI in Logistics: Smarter Inventory and Shipment Optimization

Author

Listed:
  • Samuel Tatipamula

Abstract

Artificial intelligence is revolutionizing logistics operations, transforming traditional supply chain processes into dynamic, data-driven systems that continuously adapt to changing conditions. This technical article explores how AI technologies are addressing critical inefficiencies in inventory management and shipment optimization that have historically plagued logistics operations. Advanced machine learning algorithms now enable unprecedented demand forecasting accuracy, dynamic inventory optimization, and intelligent route planning that considers multiple constraints simultaneously. These systems process real-time data from diverse sources to generate actionable insights that balance competing priorities such as cost reduction, service level improvements, and sustainability goals. The implementation of AI-powered solutions, while facing challenges including data quality issues and organizational resistance, offers substantial competitive advantages through reduced operational costs, improved delivery precision, and enhanced customer satisfaction. As technologies including digital twins, autonomous vehicles, blockchain, and quantum computing continue evolving, they promise to further transform logistics operations into increasingly automated and resilient systems capable of self-optimization.

Suggested Citation

  • Samuel Tatipamula, 2025. "AI in Logistics: Smarter Inventory and Shipment Optimization," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 11(2), pages 3352-3373, March.
  • Handle: RePEc:jbh:ijsrcs:v11:y2025:i2:id:1381
    DOI: 10.32628/CSEIT25112813
    Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT25112813
    as

    Download full text from publisher

    File URL: https://ijsrcseit.com/home/article/view/CSEIT25112813
    File Function: Article URL
    Download Restriction: no

    File URL: https://ijsrcseit.com/home/article/download/CSEIT25112813/CSEIT25112813
    File Function: Full text
    Download Restriction: no

    File URL: https://libkey.io/10.32628/CSEIT25112813?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:jbh:ijsrcs:v11:y2025:i2:id:1381. 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 (USA) (email available below). General contact details of provider: https://ijsrcseit.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.