Research on the Route Planning Problem of Drone and Truck Collaborative Delivery in Restricted Areas

Aiming at the low efficiency of logistics distribution and the problem of restricted areas, we develop a collaborative distribution model that integrates trucks and drones, allowing for single takeoff and multiple drone deliveries. By considering the restricted areas for trucks and drones, a mathematical model has been constructed and a multi-stage heuristic optimization algorithm is proposed. This algorithm combines ant colony algorithm and simulated annealing algorithm, and a variety of neighborhood generation operators are introduced to improve the optimization effect. The model and algorithm are verified by different examples. Results show that the average solutions of algorithm is efficiency higher than Guorbi in small-scale instance, compared with the traditional truck distribution, the collaborative distribution shrink the 22.3% distribution time on average. Additionally, the increase in the restricted area customers and truck numbers has a significant impact on the complexity of route planning and distribution efficiency. Our research results can provide valuable guidance for future drone participation in complex urban and rural logistics distribution scenarios.