Location optimization of urban fire stations: Access and service coverage

Abstract Fire and rescue services are among the most critical public services provided by governments to protect people, property and the environment from fires and other emergencies. Efficient deployment of fire stations is essential to ensure timely response to calls for service. Given the geographic nature of such problems, spatial optimization approaches have long been employed in public facility location modeling along these lines. In particular, median and coverage approaches have been widely adopted to help achieve travel-cost and service-coverage goals, respectively. This paper proposes a bi-objective spatial optimization model that integrates coverage and median goals in the service of demand areas. Based on the properties of derived objective functions, we presented a constraint-based solution procedure to generate the Pareto frontier, enabling the identification of alternative fire station siting scenarios. The developed model is applied to an empirical study that seeks to identify the best fire station locations in Nanjing, China. The results demonstrate the value of spatial optimization in assisting fire station planning and rescue resource deployment, highlighting important policy implications.