Abstract: To address the challenge of limited drone range in executing long-distance transportation tasks,a segmented relay-based drone logistics network planning method is proposed,utilizing a genetic algorithm.This method comprehensively considers logistics demand and drone range limitations,aiming to minimize construction and operational costs.By designing network connectivity judgment loops,evaluation index judgment loops,and iterative objective judgment loops,it achieves intelligent optimization of the drone logistics network structure.The algorithm incorporates four operators that effectively control the number and location of relay nodes,enabling the planning solution to progressively approach the global optimum.Through the construction of an agent-based simulation model,it is demonstrated that the drone logistics network generated by this method can economically and efficiently meet logistics demand,particularly suitable for long-distance urban transportation or logistics network planning in remote mountainous areas.This method provides an innovative solution for the green and efficient operation of drone logistics networks.

Key words: Network planning, Unmanned aerial vehicle, Low-altitude economy, Range-constrained