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<p>Truck-drone delivery systems have the potential to improve how
the logistics industry approaches the “last mile problem”. For the purposes of
this study, the “last mile” refers to the portion of the journey between the
last transportation hub and the individual customer that will consume the product.
Drones can deliver packages directly, without the need for an underlying
transportation network but are limited by their range and payload capacity. Studies
have developed multiple truck-drone configurations, each with different
approaches to leverage the benefits and mitigate the limitations of drones.
Existing research has also established the drone’s reduction to package
delivery time over the traditional truck only model. Two key model factors that
have not been considered in previous research are the distribution of package
demand, and the distribution of package weight. This study analyzes the drone’s
impact to the energy efficiency of a package delivery system, which has taken a
backseat to minimizing delivery time. Demand distribution dictates the travel
distances required for package delivery, as well as the proportion of delivery
locations that are in range for drone delivery. Package weight determines the
energy consumption of a delivery and further restricts the proportion of drone
eligible packages. The major contributions of this study are the development of
a truck-drone tandem mathematical model which minimizes energy consumption, the
construction of a population-based package demand distribution, a realistic package
weight distribution, and a genetic algorithm used to solve the mathematical
model developed for problems that are too computationally expensive to be
solved optimally using an exact method. Results show that drones can only have
a significant impact to energy efficiency in package delivery systems if
implemented under the right conditions. Using truck-drone tandem systems in areas
with lower package demand density affords the drone the potential for larger
energy savings as larger portions of the truck distance can be replaced.
Further, the lower density translates to greater differences between the
road-restricted driving distance and the flying distance between delivery points.
Finally, energy savings are highly dependent on the underlying package weight
distribution of the system. A heavier average package weight increases the
energy consumption of the system, but more importantly the portion of packages
above the drone’s payload capacity severely limit the savings afforded by the
incorporation of drones. </p>
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| Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/8028974 |
| Date | 10 June 2019 |
| Creators | Juan Carlos Orozco (6623699) |
| Source Sets | Purdue University |
| Detected Language | English |
| Type | Text, Thesis |
| Rights | CC BY 4.0 |
| Relation | https://figshare.com/articles/Analysis_of_Energy_Efficiency_in_Truck-Drone_Last_Mile_Delivery_Systems/8028974 |
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