Path Optimization of Biological Control of Mosquitoes in UAV Based on Particle Swarm Optimization

Particle Swarm Optimization (PSO) is an optimization algorithm for computer manual search. Many diseases such as malaria, dengue fever and Zika fever around the world seriously threaten human health. The main vectors are harmful mosquitoes such as Anopheles, especially in vast areas such as grasslands. In recent years, mosquitoes carrying Wolbach's bacteria can effectively control mosquitoes. This paper studies the application of particle swarm optimization (PSO) to calculate the path of unmanned aerial vehicle (UAV) to release mosquitoes. From the actual situation, it analyzes the advantages and disadvantages of PSO, designs the constraint conditions and objective functions, and establishes the model of PSO. In view of the fact that this algorithm is prone to premature convergence and falling into the local optimal solution, it is reformed by setting the strategy of linear decreasing value of inertia factor. Compared with the traditional PSO, it can reduce the delivery time, improve the delivery efficiency and reduce the delivery distance.