Exact and heuristic approaches to truck–drone delivery problems.
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Date
2023
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Abstract
Collaborative delivery employing drones in last-mile delivery has been an extensively studied topic in recent
years. In this paper, it is studied Truck–Drone Delivery Problems (TDDPs) in which a traditional delivery truck
is gathered with a drone to cut delivery times and costs. The vehicles work together in a hybrid operation
involving one drone launching from a larger vehicle that operates as a mobile depot and a recharging platform.
The drone launches from the truck with a single package to deliver to a customer. Each drone must return to
the truck to recharge batteries, pick up another package, and launch again to a new customer location. This
work proposes a novel Mixed Integer Programming (MIP) formulation and a heuristic approach to address
the problem. The proposed MIP formulation yields better linear relaxation bounds than previously proposed
formulations for all instances, and was capable of optimally solving several unsolved instances from the
literature. A hybrid heuristic based on the General Variable Neighborhood Search metaheuristic combining
Tabu Search concepts is employed to obtain high-quality solutions for large-size instances. The efficiency of
the algorithm was evaluated on 1415 benchmark instances from the literature, and over 80% of the best known
solutions were improved.
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Keywords
Unmanned aerial vehicle, Traveling salesman problem, Mixed-integer programming, General variable neighborhood search
Citation
FREITAS, J. C. de; PENNA, P. H. V.; TOFFOLO, T. A. M. Exact and heuristic approaches to truck–drone delivery problems. EURO Journal on Transportation and Logistics, v. 12, artigo 100094, 2023. Disponível em: <https://www.sciencedirect.com/science/article/pii/S219243762200019X>. Acesso em: 06 jul. 2023.