Genetic algorithm for the strategic location of a network of fire hydrants

Abstract

In Trujillo, a norther city from Peru, the number of fire hydrants is currently 497; only 10% are working out in the center of this city. Faced with this situation, the firefighters do not attend in optimum time the various emergencies happen, making possible the increase of material damages and victims due to the lack of water supply caused by the inoperativeness hydrants and also a non-optimum distribution. In this research, a network of hydrants was strategically located through the design and output of a genetic algorithm, GA. There are many solutions, and only one individual must be selected, the most efficient. It was evaluated by the fitness function about the length from a common point to others where the hydrants are, and the best solution was determined by applying genetic operators like crossover and mutation, which means the location points of the hydrants on the map of the city. The result shows a very good solution for a hydrant network; in addition, the number of hydrants that make up the network with the average distance of the network that reduce the time to attend an emergency. The result shows a very good solution for a hydrant network; the number of hydrants that make up the network with the average distance of the network reduces the time to attend an emergency. It will be useful to redistribute the hydrants for better locations.