Two-Stage Robust Facility Location Problem with Drones
Published In
Transportation Research Part C-Emerging Technologies
Document Type
Citation
Publication Date
4-1-2022
Abstract
The past few years have witnessed the increasing adoption of drones in various industries such as logistics, agriculture, military, and telecommunications. This paper considers a short-term post-disaster unmanned aerial vehicle (UAV) humanitarian relief application where first-aid products need to be delivered to the customer demand points. The presented problem, two-stage robust facility location problem with drones (two-stage RFLPD), incorporates the demand uncertainty using demand scenarios. This problem aims to find a location–allocation-assignment plan that has minimal two-stage total cost in the worst-case scenario of all the possible demand outcomes. Three different models of the problem are proposed, two of which incorporate a realistic UAV electricity consumption model while the last one has greater operational flexibility. The column-and-constraint generation method and Benders decomposition are used to solve the two models, and a thorough comparison among the deterministic facility location problem with drones (FLPD) models and three proposed models are also presented. Numerical analysis results show that the proposed model has significantly less average cost in the simulation runs compared to the deterministic FLPD.
Rights
Copyright © 2022 Elsevier B.V.
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DOI
10.1016/j.trc.2022.103563
Persistent Identifier
https://archives.pdx.edu/ds/psu/37543
Citation Details
Zhu, Tengkuo, Stephen D. Boyles, and Avinash Unnikrishnan. "Two-stage robust facility location problem with drones." Transportation Research Part C: Emerging Technologies 137 (2022): 103563.