Multi-UAVs Pickup and Delivery Problem: Minimizing Maximum Energy Consumption

Cargo Unmanned Aerial Vehicles (UAVs) have been increasingly utilized in short-distance logistics scenarios within urban environments. This paper delves into the path planning problem for multi-user pickup and delivery operations of UAVs. The UAVs embark from a depot, execute the pickup and delivery tasks, and subsequently return to the depot, all while maintaining a reliable connection with the ground base station (GBS) throughout their flight. The energy consumption of the UAVs is intricately tied to the sequence of pickup and delivery, as well as the weight of the transported goods. To minimize the maximum energy consumption of the UAVs and optimize their flight trajectories, this paper focuses on optimizing the access sequence. Firstly, we construct a radio map of the target area, enabling us to assess communication reliability. Subsequently, we introduce an enhanced Dijkstra’s algorithm to compute the shortest paths between any two access points that ensure reliable communication. Then, we devise a chromosome structure tailored for a hybrid genetic algorithm (HGA), specifically addressing the multi-UAV pickup and delivery problem. Leveraging the constructed distance matrix and the designed chromosome structure, we apply the HGA to solve the problem of minimizing the maximum energy consumption during multi-UAV pickup and delivery operations. Finally, we validate the effectiveness of our proposed method through simulation results.