Multi-Cycle Emergency Material Dispatch Considering the Impact of Psychological Anxiety Under Public Health Emergencies

In this paper, we establish a quantitative function to describe the psychological anxiety of people during the COVID19 outbreak. It considers the impact of the shortage rate of emergency supplies, the dynamic number of new confirmed cases and the sensitivity of emergency supplies. On this basis, a multicycle multi-objective emergency supplies dispatching model is constructed with the objective of minimizing logistics costs and psychological anxiety costs. Then the model is solved using a fast non-dominated ranking genetic algorithm. Finally, numerical experiments were conducted using the COVID-19 outbreak in Hubei Province in 2020 as a case study. The results show that the proposed model and algorithm can effectively solve the multicycle emergency supplies distribution problem when considering the psychological anxiety in an epidemic environment. Compared with the basic emergency supplies dispatching model, results show that the proposed model can effectively reduce 60.50% psychological anxiety cost only with 8.66% increase in logistics cost. Further sensitivity analysis show that the psychological anxiety cost increased by 67.27% when reducing one unit of emergency supplies. The findings of this paper will help emergency management departments to better develop emergency supplies dispatch plans during public health emergencies.