IDEAS home Printed from https://ideas.repec.org/a/eee/jaitra/v134y2026ics0969699726000141.html

Environmental sustainability and risk-aware optimization in hybrid truck-drone logistics: A holistic multi-objective framework

Author

Listed:
  • Mahmoodi, Armin
  • Sajadi, Seyed Mojtaba
  • Laliberte, Jeremy
  • Easa, Said M.

Abstract

Compared to conventional truck-only systems, hybrid truck–drone delivery systems offer transformative potential for last-mile logistics by addressing operational inefficiencies, minimizing environmental impact, and enhancing safety through risk-aware optimization. This study develops a stochastic multi-objective optimization framework grounded in the Specific Operations Risk Assessment (SORA) methodology. By extending the vehicle routing problem with pickup and delivery (VRPPD) and the flying sidekick traveling salesman problem (FSTSP), the model incorporates battery optimization, CO2 emissions reduction, and energy-efficient routing strategies. Delivery cost, time, energy consumption, operational risk, and battery performance are all optimized using a mixed-integer linear programming (MILP) and non-dominated sorting genetic algorithm II (NSGA-II) technique. Sensitivity analysis show that increasing drone fleet size and efficiency results in significant cost, time, and energy savings while improving safety. The model's flexibility in both urban and remote delivery contexts is confirmed by numerical trials. In line with life cycle analysis (LCA), this study offers practical advice for environmentally responsible and risk-aware logistics, assisting decision-makers and industry participants in the development of scalable and sustainable solutions.

Suggested Citation

  • Mahmoodi, Armin & Sajadi, Seyed Mojtaba & Laliberte, Jeremy & Easa, Said M., 2026. "Environmental sustainability and risk-aware optimization in hybrid truck-drone logistics: A holistic multi-objective framework," Journal of Air Transport Management, Elsevier, vol. 134(C).
    • Handle: RePEc:eee:jaitra:v:134:y:2026:i:c:s0969699726000141
    DOI: 10.1016/j.jairtraman.2026.102978
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0969699726000141
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jairtraman.2026.102978?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:eee:jaitra:v:134:y:2026:i:c:s0969699726000141. 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.journals.elsevier.com/journal-of-air-transport-management/ .

    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.