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.
@InProceedings{behroozi_et_al:OASIcs.ATMOS.2020.17, author = {Behroozi, Mehdi and Ma, Dinghao}, title = {{Crowdsourced Delivery with Drones in Last Mile Logistics}}, booktitle = {20th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2020)}, pages = {17:1--17:12}, series = {Open Access Series in Informatics (OASIcs)}, ISBN = {978-3-95977-170-2}, ISSN = {2190-6807}, year = {2020}, volume = {85}, editor = {Huisman, Dennis and Zaroliagis, Christos D.}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ATMOS.2020.17}, URN = {urn:nbn:de:0030-drops-131539}, doi = {10.4230/OASIcs.ATMOS.2020.17}, annote = {Keywords: Last-mile delivery, Drone delivery, Sharing Economy} }
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