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Cited by 391

The DOI matches its Crossref record; 49 of the 49 references it cites were found in a registry or an index.

Impact of drone delivery on sustainability and cost: Realizing the UAV potential through vehicle routing optimization

Chiang, Wen-Chyuan, Li, Yuyu, Shang, Jennifer, Urban, Timothy L.·2019·Applied Energy
DOI 10.1016/j.apenergy.2019.03.117
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Abstract

Abstract An unmanned aerial vehicle (UAV), commonly known as a drone, offers the advantage of speed, flexibility, and ease in delivering goods to customers. They are particularly useful for tasks that are dull, hazardous, or dirty. Whether the use of drone delivery is beneficial to the environment and cost saving is still a topic under debate. Ideally, drones yield lower energy consumption and reduce greenhouse gas emissions, thus reducing the carbon footprint and enhancing environmental sustainability. In this research, we analytically study the impact of UAVs on CO2 emission and cost. We propose a mixed-integer (0–1 linear) green routing model for UAV to exploit the sustainability aspects of the use of UAVs for last-mile parcel deliveries. A genetic algorithm is developed to efficiently solve the complex model, and an extensive experiment is conducted to illustrate and validate the analytical model and the solution algorithm. We find that optimally routing and delivering packages with UAVs would save energy and reduce carbon emissions. The computational results strongly support the notion that using UAVs for last-mile logistics is not only cost effective, but also environmentally friendly.

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Metadata

Authors
Chiang, W.-C., Li, Y., Shang, J., & Urban, T. L.
Venue
Applied Energy
Publisher
Elsevier BV
Published
2019-05
Volume
242
Pages
1164-1175
ISSN
0306-2619 (ISSN-L)
DOI
10.1016/j.apenergy.2019.03.117
OpenAlex
W2935841433
Cited by
391
References
49
FWCI
22.49
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Impact of drone delivery on sustainability and cost: Realizing the UAV potential through vehicle routing optimization. https://app.cochat.ai/papers/10.1016/j.apenergy.2019.03.117
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Chiang, W.-C., Li, Y., Shang, J., & Urban, T. L. (2019). Impact of drone delivery on sustainability and cost: Realizing the UAV potential through vehicle routing optimization. Applied Energy. https://doi.org/10.1016/j.apenergy.2019.03.117

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.