A comparative analysis of synchronized truck-and-drone delivery models. (December 2021)

• Record Type: Journal Article
• Authors: Moshref-Javadi, Mohammad; Hemmati, Ahmad; Winkenbach, Matthias
• Is Part Of: Computers & industrial engineering. Volume 162(2021)
• Publication Date: 2021-12
• Subjects: Drone logistics -- Routing optimization -- Last-mile delivery -- Mathematical model -- Metaheuristic; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2021.107648
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: We evaluate and compare three truck-and-drone delivery models. We mathematically model three truck-and-drone delivery models. We use TDRA, a flexible metaheuristic algorithm which can solve the three underlying routing problems. We conduct comprehensive evaluation of the models on five problem sets. We compare the models and quantify the benefits by each model. Abstract: In this paper, we conduct a comparative analysis of three synchronized truck-and-drone delivery models for package delivery. In these models, drones are launched from the truck to deliver packages and return to the truck after delivery. The considered models vary with respect to the level of synchronization between the truck and the drones. We mathematically formulate the associated routing problems and prove theoretical bounds on the maximum possible savings that can be obtained by these models compared to truck-only routes. Further, we use a Truck and Drone Routing Algorithm (TDRA), which we use to evaluate these models on four sets of problem instances, as well as two realistic case studies. Our numerical results indicate that a higher level of synchronization considerably leads to reduced customer waiting times. The results of our case study analysis also show that these models can obtain more than 60% customer waiting time reduction compared to a truck-only scenario although the percentage of reduction depends on the values of the underlying parameters of the problem, such as the number of drones, the drone to truck speed ratio, and the drone flight time limit.