The vehicle routing problem with drones: Extended models and connections
By Stefan Poikonen, Xingyin Wang, Bruce L. Golden. Networks, 2017
325 citations recorded by the source corpus.
Subfields: Automotive Engineering, Computer Networks and Communications, Industrial and Manufacturing Engineering
View Paper: https://www.semanticscholar.org/paper/94baab1c44d23822ce7681f7b49240dbb30e18e6
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Automotive Engineering
- Gilbert Laporte
- Thibaut Vidal
- Stefan Røpke
- David Pisinger
- David Sacramento
- Piotr Matl
- M. Moshref-Javadi
- Matthias Winkenbach
In Computer Networks and Communications
- Gilbert Laporte
- James F. Campbell
- Stefan Røpke
- Bruce L. Golden
- David Pisinger
- Niels A. H. Agatz
- Erwin Pesch
- Alena Otto
In Industrial and Manufacturing Engineering
- Gilbert Laporte
- Thibaut Vidal
- Stefan Røpke
- David Pisinger
- Matthias Winkenbach
- M. Moshref-Javadi
- David Sacramento
- Jean-François Cordeau
Citations in the corpus
- Dynamic programming approaches for the traveling salesman problem with drone (2017, unknown): “[18] analyze the theoretical benefits of using one or more drones together with one or more delivery vehicles to make deliveries.”
- Applications and Research avenues for drone-based models in logistics: A classification and review (2021, background): “In a later study by Poikonen et al. (2017), the worst-case analysis is extended to take into account travel range limits, different travel time metrics, and more general cost objective functions.”
- An adaptive large neighborhood search metaheuristic for the vehicle routing problem with drones (2019, background): “This work is extended by Poikonen et al. (2017) where the effect of limited drone battery life and the effect of having two different distance matrices for the trucks and drones are considered.”
- Optimization approaches for civil applications of unmanned aerial vehicles (UAVs) or aerial drones: A survey (2018, background): “[215] also examine maximum potential savings in the case of different distance metrics for trucks and drones, in the case of a limited battery life, and for a general objective function that considers not only the makespan, but also variable costs of truck and drone deployment per unit of time.”
- A concise guide to existing and emerging vehicle routing problem variants (2019, background): “, drones (Poikonen et al. 2017) or autonomous vehicles (Fagnant and Kockelman 2015), or to the redesign of business models and supply chains, e.”