Designing Resilient Drone Delivery Infrastructure: A Robust Facility Location Approach

Zhiqiang Niu (), Cui Cai (), Junbo Wang (), Jing Ye (), Mengfei Cao () and Sicong Li ()
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Zhiqiang Niu: Ministry of Transport Research Institute of Highways, Research Center of Logistics
Cui Cai: Ministry of Transport Research Institute of Highways, Research Center of Logistics
Junbo Wang: Ministry of Transport Research Institute of Highways, Research Center of Logistics
Jing Ye: Ministry of Transport Research Institute of Highways, Research Center of Logistics
Mengfei Cao: Ministry of Transport Research Institute of Highways, Research Center of Logistics
Sicong Li: Ministry of Transport Research Institute of Highways, Research Center of Logistics

A chapter in Proceedings of the 2025 7th International Conference on Economic Management and Model Engineering (ICEMME 2025), 2026, pp 382-390 from Springer

Abstract: Abstract Drone-based last-mile delivery is highly sensitive to demand uncertainty and constrained by limited battery capacity, making the strategic location of drone bases critical. This study proposes a robust facility location model that jointly optimizes facility siting, drone assignment, and customer allocation under these challenges. The model guarantees full service coverage and respects hard battery and capacity constraints for all demand realizations within a budgeted uncertainty set. Computational results on a 50-customer instance show that the worst-case total cost exhibits a stepwise increase as the uncertainty budget grows. This non-smooth cost behavior suggests that maintaining feasibility under higher uncertainty levels may require discrete adjustments to the infrastructure, such as opening additional facilities. Our approach provides a practical tool for designing drone networks that are both cost-effective and provably resilient.

Keywords: Drone delivery; UAV; robust; location (search for similar items in EconPapers)
Date: 2026
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DOI: 10.2991/978-94-6239-602-9_35

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