A Variable Neighborhood Search for Flying Sidekick Traveling Salesman Problem
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An innovative model of parcel distribution is emerging from the accelerated evolution of drones and the effort of logistic companies to proceed faster deliveries at a reduced cost. This new modality originated the Flying Sidekick Traveling Salesman Problem (FSTSP) in which customers are served either by a truck or a drone. Additionally, this variant of the Traveling Salesman Problem (TSP) presents several new restrictions concerning the drone such as endurance and payload capacity. This work proposes a hybrid heuristic that the initial solution is created from the optimal TSP solution reached by a Mixed-Integer Programming (MIP) 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 total delivery time up to 67.79 established for all FSTSP instances that results are reported in the literature. Furthermore, a new set of instances based on well-known TSPLIB instances is provided.
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