Creative Commons Attribution 3.0 Unported license (CC-BY 3.0)when quoting this document, please refer to the following
DOI: 10.4230/OASIcs.ATMOS.2020.17
URN: urn:nbn:de:0030-drops-131539
URL: https://drops.dagstuhl.de/opus/volltexte/2020/13153/
Behroozi, Mehdi ; Ma, Dinghao
Crowdsourced Delivery with Drones in Last Mile Logistics
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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.
BibTeX - Entry
@InProceedings{behroozi_et_al:OASIcs:2020:13153,
author = {Mehdi Behroozi and Dinghao Ma},
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 = {OpenAccess Series in Informatics (OASIcs)},
ISBN = {978-3-95977-170-2},
ISSN = {2190-6807},
year = {2020},
volume = {85},
editor = {Dennis Huisman and Christos D. Zaroliagis},
publisher = {Schloss Dagstuhl--Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/opus/volltexte/2020/13153},
URN = {urn:nbn:de:0030-drops-131539},
doi = {10.4230/OASIcs.ATMOS.2020.17},
annote = {Keywords: Last-mile delivery, Drone delivery, Sharing Economy}
}
| Keywords: | Last-mile delivery, Drone delivery, Sharing Economy | |
| Seminar: | 20th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2020) | |
| Issue date: | 2020 | |
| Date of publication: | 10.11.2020 |
