A novel framework incorporating socioeconomic variables into the optimisation of South East Queensland fire stations coverages

Socioeconomic factors can vary the demand for fire services. Consequently, shifts in the socioeconomic make-up of a population may deem the historical data of the services’ demand less relevant. Unfortunately, studies on facility coverages have not considered the relevant socioeconomic variables. There are also minimal studies on covering location models that cater to sparse patches of residents around urban centres. Hence, this paper proposes a framework incorporating socioeconomic variables while optimising fire station coverages in South East Queensland, Australia. A robust backward stepwise regression analysis is first adopted to form a predictive socioeconomic equation of building fires. Then, a mathematical model embedding the equation is presented, along with a modification to minimise the distances between uncovered demand areas and their closest facilities. The potential algorithm to solve the model is also proposed. The research is the first to embed socioeconomic variables into a covering location problem. In the long run, wide adoption of the framework is expected to provide more equitable emergency services coverage to communities worldwide.