China Safety Science Journal ›› 2023, Vol. 33 ›› Issue (4): 194-201.doi: 10.16265/j.cnki.issn1003-3033.2023.04.0886

• Technology and engineering of disaster prevention and mitigation • Previous Articles     Next Articles

Warehouse site selection of emergency epidemic prevention materials based on metapopulation SIR model

JIANG Xiaoyi(), HE Ketai, JING Haosheng   

  1. School of Mechanical Engineering, Beijing University of Science and Technology, Beijing 100083, China
  • Received:2022-11-11 Revised:2023-02-12 Online:2023-04-28 Published:2023-10-28

Abstract:

In order to improve the emergency response and control level of the epidemic situation, the location method of emergency epidemic prevention material reserve warehouse was studied. Firstly, considering the population in the urban network and the flow of people between cities, the composite population SIR model was used to predict the demand for emergency epidemic prevention materials, and the accuracy of the prediction was verified by the urban influenza data in North China in 2017. Then, the initial solution space was generated by rasterizing location area. Based on the principle of timeliness priority, a large-scale regional reserve warehouse location model based on p-median model was constructed. With the goal of minimizing the weighted transportation distance, an elite retention genetic algorithm combined with the center of gravity method was designed to solve the model. Finally, taking the construction of epidemic prevention material warehouse in North China as an experimental case, the validity of the model and algorithm was verified by using real transportation distance data. The results show that when the candidate location of the warehouse in a large-scale area is unknown, the model and the algorithm can ensure the rationality and computational agility of the location scheme, and meet the supply demand of emergency epidemic prevention materials under the condition of limited number of warehouses.

Key words: metapopulation, susceptible infected recovered(SIR) model, emergency epidemic prevention materials, warehouse site selection, P-median model, genetic algorithm