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

Author:
Chiang, Wen-Chyuan, Li, Yuyu, Shang, Jennifer, Urban, Timothy L.
Source:
Applied energy 2019 v.242 pp. 1164-1175
ISSN:
0306-2619
Subject:
algorithms, carbon, carbon dioxide, carbon footprint, consumers (people), cost effectiveness, energy, greenhouse gas emissions, models, unmanned aerial vehicles
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.
Agid:
6346318