Multi-Algorithm-Based UAV Routing Optimization for Low-Altitude Logistics Scenarios

Unmanned Aerial Vehicles (UAVs) are now indispensable in low altitude urban logistics for their efficiency and versatility. In order to boost their practical performance in such a mission, in this paper, we study three typical UAV dispatching problems: (1) single UAV routing with battery constraints, (2) multi UAV task allocation and routing balance and (3) multi UAV minimization of UAVs with hard time window constrains. The mathematical models of each case are constructed, and the optimization algorithm such as greedy algorithm, cluster algorithm, genetic algorithm and simulated annealing algorithm are designed for each case. The simulation shows that greedy algorithm has better optimization in resource utilization and the convergence of the simulated annealing algorithm is better under the complex constraints. This results provide an algorithmic insight for the improved UAV scheduling problem in MUCLL environment.