A hybrid variable neighborhood search heuristic for the sustainable time-dependent truck-drone routing problem with rendezvous locations

As an innovative approach to city logistics, the truck and drone delivery systems piqued the interest of academia and various companies in recent years, which takes advantage of both trucks’ large capacity and drones’ high speed. In congested city areas, dense traffic significantly impacts delivery time and all three sustainable dimensions (economic, environmental, and social) of delivery systems. For this reason, we focused on the sustainable time-dependent truck and drone routing problem with rendezvous locations. This work processes with a hybrid variable neighborhood search algorithm. We carried out numerous computational experiments to evaluate the performance of the proposed algorithm, and the results show its efficiency. Finally, by performing a detailed sensitivity analysis, the result highlights that the proposed model can reduce the completion time, operational costs, truck emissions, and social penalties in comparison to the flying sidekick traveling salesman model.