Path Planning Method in Taigu County Based on the Hybrid Ant Colony Optimization-Genetic Algorithm in the Context of COVID-19

During the period of COVID-19, there is a mixture of areas that are susceptible to COVID-19 infection and areas that are not susceptible to COVID-19 infection in cities. Blind wandering is often accompanied by the risk of infection. Hence, in order to improve the safety of people’s travel, this paper uses the hybrid Ant Colony Optimization-Genetic Algorithm (ACO-GA) to plan the central path of Taigu County. The volatilization coefficient of pheromone in Ant Colony Optimization (ACO) is changed dynamically. Pheromones in high-risk areas that are susceptible to epidemic infection are more volatile, while pheromones in low-risk areas that are less suscep-tible to epidemic infection are less volatile. Adjust the selection of “gene” mutation in Genetic Algorithm (GA). Vulner-able areas should be closed off to cut off the source of infection. As long as the shortest route which is of lower risk is formulated, people should stay away from high-risk areas that are susceptible to infection as much as possible to reduce the spread of COVID-19 and ensure the safety of people’s lives. The path under the influence of the COVID-19 is predicted and analyzed in the form of a simulation. The experimental results show that the algorithm can help to effectively avoid areas susceptible to the COVID-19 and reduce the risk of people getting sick.