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The Drone Aided Routing Problem: Analysis of Optimization Algorithms for Last Mile Delivery

Matteo Arico'

The Drone Aided Routing Problem: Analysis of Optimization Algorithms for Last Mile Delivery.

Rel. Giorgio Guglieri, Stefano Primatesta. Politecnico di Torino, Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica), 2021

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Unmanned aerial vehicles are gaining momentum in many industrial sectors. While in some areas the use of drones has already become a standard practice, in some others research activities are still needed as the development has not reached a mature stage yet. This is where this Thesis project is aimed to insert in, dealing with the logistic problem of last mile delivery. Some companies, such as Google, UPS and Amazon, have started their own programs in order to provide drone delivery in the near future. This push from established companies has led to optimism in the sector, as employing drones for this purpose looks promising. Indeed, several works handled the truck and drone routing delivery problem. Cooperation between them to deliver parcels has already been proven to be effective in terms of delivery time, costs and emissions. Most importantly, drones are extremely effective when fast speeds of delivery are necessary, as for example for medical goods shipment, since they are not subject to road network restrictions and traffic. This work performs an analysis of some approaches already proposed in the literature in order to build an optimization algorithm able to find an optimal solution where a set of customers needs to be served by a truck and a drone. Several assumptions on the scenario need to be made and various constraints on the optimization process needs to be followed, so that a feasible solution can be obtained. Starting from this solid basis, the project is aimed at extending the scenario where a fleet of drones is employed. In this way, the solution provided by the single truck-single drone scenario is expected to be improved, even though the problem gets more complicated as the number of available vehicles increases. Insights on the tested algorithms will be provided, displaying data relevant for the solutions analysis. The advantages in terms of completion time of the delivery process obtained with respect to the well documented single truck solution will be highlighted, as well as advantages and disadvantages among the selected approaches. The Thesis concludes by providing possible improvements that can be made on the algorithms and suggesting future research perspectives.

Relators: Giorgio Guglieri, Stefano Primatesta
Academic year: 2020/21
Publication type: Electronic
Number of Pages: 94
Corso di laurea: Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica)
Classe di laurea: New organization > Master science > LM-25 - AUTOMATION ENGINEERING
Aziende collaboratrici: UNSPECIFIED
URI: http://webthesis.biblio.polito.it/id/eprint/19280
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