China Safety Science Journal ›› 2022, Vol. 32 ›› Issue (3): 183-193.doi: 10.16265/j.cnki.issn1003-3033.2022.03.025

• Public safety • Previous Articles     Next Articles

Study on location selection of linkage fire stations based on demand level and distance loss

HUO Feizhou1,2(), DONG Geli1,2, LI Moxiao1,2,**(), MEI Yiyun1,2   

  1. 1China Research Center for Emergency Management, Wuhan University of Technology, Wuhan Hubei 430070, China
    2School of Safety Science and Emergency Management, Wuhan University of Technology, Wuhan Hubei 430070, China
  • Received:2021-12-24 Revised:2022-02-11 Online:2022-08-23 Published:2022-09-28
  • Contact: LI Moxiao

Abstract:

In order to improve urban fire resistance, designing fire stations based on urban development status could be an effective means to improve firefighting efficiency and optimize allocation of resources. Firstly, regional fire potential was assessed based on population density and distribution of high-risk fire potential units, and ArcGIS was adopted to simulate distribution of fire potential and classify it. Then, with influence of fire station response distance on fire loss being taken into consideration, an optimized model of linkage fire station location selection based on demand grade and distance loss was established, and multi-objective optimization algorithm NSGA-Ⅱ was used to solve it iteratively. Finally, with Xiangzhou district, Xiangcheng district and Fancheng district of Xiangyang as examples, the model was compared with layout of fire stations in active service and that of site selection considering single factor. The results show that the optimization model comprehensively considers both factors of demand level and distance loss, and implements multi-level coverage for high-risk units according to the actual demand. As a results, it features a better location than that considering a single factor, and it proves to be more reasonable in fire resources' utilization.

Key words: demand level, distance loss, location of fire station, fire potential, multilevel coverage