A fuzzy multi-objective programming for optimization of fire station locations through genetic algorithms

The location of fire stations at a fire & rescue service is an important factor in its fire protection capability. This paper aims to determine the optimal location of fire station facilities. The method proposed here is the combination of a fuzzy multi-objective programming and a genetic algorithm. The reason of using this method is that the decision of where to locate fire stations depends upon a set of criteria, such as travel times or travel distances, setting up costs and operating costs, and the ordinary optimization methods may not be able to handle them effectively due to the relatively large scale of real problems. The original fuzzy multiple objectives are appropriately converted to a single unified ‘min-max’ goal, which makes it easy to apply a genetic algorithm for the resulting problem solving. Compared with the existing methods of fire station location our approach has three distinguish features: (1) considering the fuzzy nature of a decision maker (DM) in the location optimization model; (2) fully considering the demands to the facilities from the areas with various fire risk categories; (3) being more understandable and practical to DM. The case study was based on the data collected from the Derbyshire fire & rescue service and used to illustrate the application of the method for fire station locations.