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.
Highlights
Trujillo does not prepare to withstand a major fire; many factors are involved in an emergency, like bad power connections in homes, highly inflammable materials, informal warehouses and lack of water
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
We study an optimal allocation problem; a GA was considered appropriate there are other heuristics like spotted hyena optimizer algorithm [6] where the objective function includes minimizing the energy losses cost; GA is one the best alternatives to apply when trying to solve well placement and production allocation problems like in hydrocarbon production optimization [6]
Summary
Trujillo does not prepare to withstand a major fire; many factors are involved in an emergency, like bad power connections in homes, highly inflammable materials, informal warehouses and lack of water. This problem is faced by firefighters, who use very limited and obsolete tools and materials; they must expose their lives to avoid injuries and fatalities, suffocating the fire in these cases. They must use hydrants, but these have low water power at the time of emergency, so that the only optimal water supply of hydrant is constrained at night and for some hours; worse if the hydrants are located in non-strategical points of the city. He states not having enough budget to purchase equipment and uniforms for the firefighters
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