The Last-Mile Delivery Process with Trucks and Drones Under Uncertain Energy Consumption

We address the problem of delivering parcels in an urban area, within a given time horizon, by conventional vehicles, i.e., trucks, equipped with drones. Both the trucks and the drones perform deliveries, and the drones are carried by the trucks. We focus on the energy consumption of the drones that we assume to be influenced by atmospheric events. Specifically, we manage the delivery process in a such a way as to avoid energy disruption against adverse weather conditions. We address the problem under the field of robust optimization, thus preventing energy disruption in the worst case. We consider several polytopes to model the uncertain energy consumption, and we propose a decomposition approach based on Benders' combinatorial cuts. A computational study is carried out on benchmark instances. The aim is to assess the quality of the computed solutions in terms of solution reliability, and to analyze the trade-off between the risk-adverseness of the decision maker and the transportation cost.