Truck-and-drone Collaborative Delivery Method Based on Adaptive Simulated Annealing Algorithm

The collaborative delivery of trucks and drones can comprehensively take advantage of the advantages of the two means of transportation. The emphasis of this paper lies in addressing the logistics distribution challenges associated with individual vehicles and drones. This paper established a two-level path planning model for truck and drone collaborative logistics distribution. Based on the characteristics of truck-and-drone collaborative logistics distribution problems, various specific neighborhood structures and an adaptive neighborhood selection mechanism have been meticulously designed, after that, an adaptive simulated annealing algorithm (ASA) was proposed. The results of simulation experiments demonstrate that the proposed method efficiently searches for satisfactory solutions for the collaborative delivery path between trucks and drones across various delivery ranges and quantities of packages in a relatively short timeframe. The cost of truck-and-drone collaborative delivery is reduced by approximately 50.25%, 14.13%, and 7% compared to the initial solution of truck separate delivery, vehicle machine collaborative delivery, and the optimal solution of the traditional simulated annealing algorithm, respectively. This method effectively reduces logistics delivery costs.