Location optimization of urban fire stations considering the variations in fire service demands: a bi-objective coverage model

ire stations serve as operational hubs for firefighting and rescue teams, making their spatial optimization crucial to ensure effective urban firefighting and rescue operations. The traditional coverage model overlooks the difference in service satisfaction among various demand areas within the coverage radius, making it less effective at optimizing fire station locations. This study examines the differing demands for fire services among various areas based on their levels of fire risk. We propose a bi-objective coverage (BOC) model to optimize the locations of urban fire stations by improving upon the traditional maximum coverage model and integrating it with the set coverage model. The e- constraint method was applied to solve the constructed BOC model, obtaining the Pareto optimal frontier. Then, the BOC model was applied to address the spatial optimization of fire station locations in the central urban area of Zhengzhou City. Finally, a comparative analysis was performed on the optimization outcomes and performance of both the BOC and bi-objective spatial optimization (BSO) (integrating coverage and median goals) models. The computational results of the BOC model outperformed those of the BSO model in terms of both the effective service rate and the multiple coverage rate for demand areas.