IDEAS home Printed from https://ideas.repec.org/a/ids/ijbpsc/v16y2026i3p251-273.html

Optimising intermodal and multimodal freight transport between the USA and Pakistan: a bi-objective MILP model for cost and energy trade-offs

Author

Listed:
  • Rizwan Shoukat
  • Zhang Xiaoqiang
  • Ayesha Saeed

Abstract

By juxtaposing multimodal and intermodal operations, this study aims to assist policymakers and supply chain managers in minimising the cost of logistics and improving business performance. The problem of minimising the cost of transporting freight from New York, the USA to Punjab, Pakistan is tackled using mixed-integer linear programming (MILP). We solved the optimisation problem by using a multiobjective genetic algorithm (MOGA) to identify Pareto front solutions for the cost trade-off between the two modes of transport. According to the findings, multimodal transportation (air, road, and rail) is 15% more cost-effective than intermodal transportation (air, road) when delivering less than a container unit. Additionally, this investigation's breakdown analysis reveals that road freight is the second-highest means of transportation in terms of cost, trailing only air freight. In multimodal transportation, the share is air (74%), rail (1%), and road (25%). However, air transport accounts for 60% of intermodal transportation, while road transport accounts for 40%

Suggested Citation

  • Rizwan Shoukat & Zhang Xiaoqiang & Ayesha Saeed, 2026. "Optimising intermodal and multimodal freight transport between the USA and Pakistan: a bi-objective MILP model for cost and energy trade-offs," International Journal of Business Performance and Supply Chain Modelling, Inderscience Enterprises Ltd, vol. 16(3), pages 251-273.
    • Handle: RePEc:ids:ijbpsc:v:16:y:2026:i:3:p:251-273
    as

    Download full text from publisher

    File URL: https://www.inderscience.com/link.php?id=156299
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    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:ids:ijbpsc:v:16:y:2026:i:3:p:251-273. 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=341 .

    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.