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Enhancing supply chain resilience under disaster by integrating mobile additive manufacturing and truck-drone delivery

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  • Abdolazimi, Omid
  • Ma, Junfeng

Abstract

Natural and man-made disasters disrupt supply chains, leading to delays, financial losses, and service disruptions. This study enhances supply chain resilience (SCR) by integrating mobile additive manufacturing (MAM) and truck-drone delivery (TDD) systems to facilitate rapid responses in disaster scenarios. A synchronized MAM-TDD mechanism is proposed to align on-the-move production with customer time windows. A mixed-integer linear programming (MILP) model is developed to minimize operating costs, delivery penalties, and quality degradation caused by disaster-damaged infrastructure. To address uncertainty, a scenario-based robust optimization approach is employed, and a tailored heuristic (MAM-TDD variable neighborhood descent, MTVND) is introduced to find solutions efficiently. The proposed model is benchmarked against three alternatives: MAM with truck-delivery, fixed AM (FAM) with TDD, and FAM with truck-delivery, using a real-world case study across varying disaster severities. Results show that MAM-TDD outperforms others in high-disruption scenarios by expanding delivery reach and reducing delays and costs. The findings provide actionable insights for deploying flexible, resilient logistics systems that maintain product quality and operational efficiency during disasters.

Suggested Citation

  • Abdolazimi, Omid & Ma, Junfeng, 2026. "Enhancing supply chain resilience under disaster by integrating mobile additive manufacturing and truck-drone delivery," Omega, Elsevier, vol. 142(C).
    • Handle: RePEc:eee:jomega:v:142:y:2026:i:c:s0305048326000216
    DOI: 10.1016/j.omega.2026.103532
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