Using drones for parcels delivery process

Parcels delivery is the most expensive phase of the distribution logistics. Everyday, several vehicles, usually internal combustion engine vehicles, have to serve a high number of customers spatially distributed in an urban area. Their presence generates several negative externalities, such as, noise, congestion and pollutant emissions. Drones have become a valid alternative to support the delivery process and several big companies, such as, Amazon and DHL, have started to use them for parcels deliveries. On the one hand, drones drastically reduce negative externalities, allowing a more sustainable delivery process. On the other hand, several technical aspects must be carefully taken into account. In particular, they have a limited flight endurance and capacity. In addition, several restrictions related to safety and flight area must be considered. Indeed, not all countries allow the use of drones in the urban area. In this work, we provide a qualitative and quantitative analysis on benefits and drawbacks in using drones in the parcels delivery process. We analyze three different transportation systems with incremental use of drones for the delivery. In particular, we address the problem of delivering parcels without drone, known as vehicle routing problem, the problem in which the deliveries are performed by a fleet of drones starting from the central depot, and a hybrid transportation system where the classical vehicles are equipped with drones. In the latter case, the classical vehicles perform the deliveries and the drones can get in charge some deliveries. The drone takes off from the vehicle, carries out the delivery, and lands to the same vehicle at a randevouz-location. During the drone delivery, the classical vehicle continues its work. The three transportation systems are formalized via mathematical programming models. The solutions obtained by solving the models via a general-purpose solver are compared and insights on the use of drones in the urban area are provided.