Particle swarm optimization for the Capacitated Helicopter Routing Problem

To improve the ability to prevent potential natural disasters, countries around the world are actively formulating emergency plans to protect people's lives and property. In this study, Sichuan Province was used as a case study to explore the allocation of medical supplies in a single distribution center using data from 21 cities and a storage base of medical supplies in Sichuan province. By constructing integer mixed nonlinear programming models-Planar helicopter Problem (HRP) and capacity-constrained Helicopter Routing Problem (CHRP), and using Particle Swarm Optimization (PSO) algorithm to solve the model, effective scheduling results and solutions are successfully obtained. It is found that the restriction of flight distance has a significant impact on the helicopter scheduling strategy, which in turn affects the consumption of human and material resources. The results of this study are valuable for practical applications.