Optimal Siting of Fire Stations Using GIS and ANT Algorithm

Abstract

Safety and emergency response are being given greater importance while planning infrastructure and transportation projects. This is particularly so, when transporting hazardous materials (HAZMAT) within a heavily urbanized area such as Singapore. The number and location of fire stations significantly influence the efficiency of emergency response during fire accidents. This paper presents an approach to suitably situating new fire stations, considering multiple objectives, using geographic information systems (GIS) and ANT, a novel Ant algorithm. The efficiency of the current fire station locations in covering HAZMAT transport routes is studied using a GIS. The ANT algorithm is implemented within a GIS environment to locate the additional fire stations so as to reduce the response time to an accident occurring on HAZMAT transport routes from 8to5min. Other considerations include incorporating proper distance among fire stations and maximizing the area that can be served by these fire stations in 6min. Computational experiments reveal that the proposed algorithm performs stably under different parameter settings and outperforms the conventional genetic algorithm. Furthermore, the integration of GIS with ANT offers enhanced spatial analytical capabilities, and our approach can be employed to solve further intricate optimization problems in transportation and infrastructure.