Locating fire stations using the Ant Colony Algorithm and GIS A Case study: Tehran City
Subject Areas :Mohammad Arab Amiri 1 , Mehrdad Rafiepour 2 , Mohammad SadiMesgari 3
1 - M.Sc., Faculty of Geodesy and Geomatics, K.N.Toosi University of Technology, Tehran
2 - M.Sc., Faculty of Geodesy and Geomatics, K.N.Toosi University of Technology, Tehran
3 - Ph.D., Associate Professor, department of geographic information system, Faculty of Geodesy and Geomatics, K.N.Toosi University of Technology, Tehran
Keywords: Ant Colony Algorithm, GIS, locating, fire stations,
Abstract :
The location of Fire stations plays an important role in the efficiency of these facilities during fire accidents. Therefore, in order to maximize the coverage of these stations to population centers, proper locating of these fire stations seems necessary. On the other hand, locating of fire stations and allocating population to them is a combinatorial optimization problem. Therefore, the purpose of this paper is to integrate geographic information system and a meta-heuristic algorithm based on ant colony algorithm for optimal site selection of fire stations. For this purpose, a case study was carried out in five regions of Tehran. In this study, suitable areas were firstly identified by analytical hierarchical process method which is a common multi-criteria decision making method. For this purpose, access to the main transportation routes, proximity to compatible land uses, and staying away from incompatible land uses were considered as criteria. Furthermore, the coverage of the existing stations was also considered in the final map. Then the suitable stations were selected from the prone options by the proposed ant colony algorithm. In order to select these stations, parameters include incorporating proper distance among fire stations and maximizing the population that can be served by these fire stations in the standard time, were considered. The computational results reveal that the proposed algorithm can obtain high quality solutions to such problems in a short time. The results of this paper also reveal the efficiency of this method in the optimal locating of fire stations.
