Research on Multi-UAV Logistics Distribution Model Based on Improved Particle Swarm Algorithm

In order to efficiently and reasonably complete multi-unmanned aerial vehicle (UAV) collaborative logistics distribution tasks, this paper studies the multi-UAV logistics distribution model and related path optimization algorithms. Firstly, a multi-UAV logistics distribution model was studied, a logistics distribution matrix was designed, constraints such as flight distance and maximum load were introduced, and the relationship between the three optimization indicators of flight cost, load cost and total voyage was given. On this basis, the objective function of the logistics distribution model is obtained. Secondly, an improved particle swarm optimization algorithm is proposed by adopting the elite learning strategy and dynamic parameter updating strategy, which is used to solve the multi-UAV logistics distribution model The experimental results show that the proposed improved particle swarm optimization algorithm has faster convergence speed, higher accuracy and stronger optimization capability in solving the multi-UAV logistics and distribution model, which makes the task allocation scheme more in line with the practical applications.