  In this paper, we study novel variants of the well-known two-echelon vehicle
routing problem in which a truck works on the first echelon to transport
parcels and a fleet of drones to intermediate depots while in the second
echelon, the drones are used to deliver parcels from intermediate depots to
customers. The objective is to minimize the completion time instead of the
transportation cost as in classical 2-echelon vehicle routing problems.
Depending on the context, a drone can be launched from the truck at an
intermediate depot once (single trip drone) or several times (multiple trip
drone). Mixed Integer Linear Programming (MILP) models are first proposed to
formulate mathematically the problems and solve to optimality small-size
instances. To handle larger instances, a metaheuristic based on the idea of
Greedy Randomized Adaptive Search Procedure (GRASP) is introduced. Experimental
results obtained on instances of different contexts are reported and analyzed.
