  The efficiency and dynamism of Unmanned Aerial Vehicles (UAVs), or drones,
present substantial application opportunities in several industries in the last
years. Notably, the logistic companies gave close attention to these vehicles
envisioning reduce delivery time and operational cost. A variant of the
Traveling Salesman Problem (TSP) called Flying Sidekick Traveling Salesman
Problem (FSTSP) was introduced involving drone-assisted parcel delivery. The
drone is launched from the truck, proceeds to deliver parcels to a customer and
then is recovered by the truck in a third location. While the drone travels
through a trip, the truck delivers parcels to other customers as long as the
drone has enough battery to hover waiting for the truck. This work proposes a
hybrid heuristic that the initial solution is created from the optimal TSP
solution reached by a TSP solver. Next, an implementation of the General
Variable Neighborhood Search is used to obtain the delivery routes of truck and
drone. Computational experiments show the potential of the algorithm to improve
the delivery time significantly. Furthermore, we provide a new set of instances
based on well-known TSPLIB instances.
