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Joint optimisation of drone routing and battery wear for sustainable supply chain development: a mixed-integer programming model based on blockchain-enabled fleet sharing

Author

Listed:
  • Yang Xia

    (Tsinghua University
    Tsinghua University)

  • Wenjia Zeng

    (Tsinghua University
    Tsinghua University)

  • Xinjie Xing

    (Management School University of Liverpool)

  • Yuanzhu Zhan

    (Birmingham Business School, University of Birmingham)

  • Kim Hua Tan

    (University of Nottingham)

  • Ajay Kumar

    (EMLYON Business School)

Abstract

Alongside the rise of ‘last-mile’ delivery in contemporary urban logistics, drones have demonstrate commercial potential, given their outstanding triple-bottom-line performance. However, as a lithium-ion battery-powered device, drones’ social and environmental merits can be overturned by battery recycling and disposal. To maintain economic performance, yet minimise environmental negatives, fleet sharing is widely applied in the transportation field, with the aim of creating synergies within industry and increasing overall fleet use. However, if a sharing platform’s transparency is doubted, the sharing ability of the platform will be discounted. Known for its transparent and secure merits, blockchain technology provides new opportunities to improve existing sharing solutions. In particular, the decentralised structure and data encryption algorithm offered by blockchain allow every participant equal access to shared resources without undermining security issues. Therefore, this study explores the implementation of a blockchain-enabled fleet sharing solution to optimise drone operations, with consideration of battery wear and disposal effects. Unlike classical vehicle routing with fleet sharing problems, this research is more challenging, with multiple objectives (i.e., shortest path and fewest charging times), and considers different levels of sharing abilities. In this study, we propose a mixed-integer programming model to formulate the intended problem and solve the problem with a tailored branch-and-price algorithm. Through extensive experiments, the computational performance of our proposed solution is first articulated, and then the effectiveness of using blockchain to improve overall optimisation is reflected, and a series of critical influential factors with managerial significance are demonstrated.

Suggested Citation

  • Yang Xia & Wenjia Zeng & Xinjie Xing & Yuanzhu Zhan & Kim Hua Tan & Ajay Kumar, 2023. "Joint optimisation of drone routing and battery wear for sustainable supply chain development: a mixed-integer programming model based on blockchain-enabled fleet sharing," Annals of Operations Research, Springer, vol. 327(1), pages 89-127, August.
    • Handle: RePEc:spr:annopr:v:327:y:2023:i:1:d:10.1007_s10479-021-04459-5
    DOI: 10.1007/s10479-021-04459-5
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    Cited by:

    1. Ali Emrouznejad & Soumyadeb Chowdhury & Prasanta Kumar Dey, 2023. "Blockchain in operations and supply Chain Management," Annals of Operations Research, Springer, vol. 327(1), pages 1-6, August.
    2. Dukkanci, Okan & Campbell, James F. & Kara, Bahar Y., 2024. "Facility location decisions for drone delivery: A literature review," European Journal of Operational Research, Elsevier, vol. 316(2), pages 397-418.
    3. Ansari, Nadia & Fattahi, Parviz & Shiri, Mahdyeh, 2025. "The role of drone technology and application of IoT on vaccine supply chain during a pandemic under uncertain Environment: A real case study of COVID-19 in Iran," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 193(C).

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