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Crowdsourced Delivery with Drones in Last Mile Logistics

Authors Mehdi Behroozi , Dinghao Ma

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Subject Classification

ACM Subject Classification
  • Applied computing → Transportation
Keywords
  • Last-mile delivery
  • Drone delivery
  • Sharing Economy

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Abstract

We consider a combined system of regular delivery trucks and crowdsourced drones to provide a technology-assisted crowd-based last-mile delivery experience. We develop analytical models and methods for a system in which package delivery is performed by a big truck carrying a large number of packages to a neighborhood or a town in a metropolitan area and then assign the packages to crowdsourced drone operators to deliver them to their final destinations. A combination of heuristic algorithms is used to solve this NP-hard problem, computational results are presented, and an exhaustive sensitivity analysis is done to check the influence of different parameters and assumptions.

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Mehdi Behroozi and Dinghao Ma. Crowdsourced Delivery with Drones in Last Mile Logistics. In 20th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2020). Open Access Series in Informatics (OASIcs), Volume 85, pp. 17:1-17:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020) https://doi.org/10.4230/OASIcs.ATMOS.2020.17

Author Details

Mehdi Behroozi
  • Department of Mechanical and Industrial Engineering, Northeastern University, Boston, MA, USA
Dinghao Ma
  • Department of Mechanical and Industrial Engineering, Northeastern University, Boston, MA, USA

Funding

Authors thank the National Science Foundation and Northeastern University for supporting this research.
  • Behroozi, Mehdi: Authors thank the National Science Foundation and Northeastern University for supporting this research.

Acknowledgements

Authors would like to thank Northeastern University’s SHARE Group for creating an environment in which this research could be accomplished.

References

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