INTRODUCING A NEW MODEL FOR LOCATING THE LOCATION OF FIREFIGHTING FORCES BASED ON FUZZY REGION AND NONDOMINATED SORTING GENETIC ALGORITHM

Abstract

The establishment of fire stations is considered an essential part of the security of any city. At the time of an accident, the location of fire stations is essential for timely and quick relief. The delay in providing aid causes irreparable damage to the life and property of the city's people, and the correct location of fire stations can prevent such incidents from happening, which is necessary to achieve this goal. It is systematic and integrated based on a suitable model. Therefore, in this research, a suitable model for locating the position of firefighting forces based on fuzzy logic and mutated genetic algorithm is proposed, which has two objective functions: one for optimizing the urban coverage and the other for optimizing Building the number of fires stations. The goal is to deploy stations in such a way as to create maximum urban coverage, and on the other hand, considering the cost of deploying each station, the method seeks to reduce the number of stations. The criteria needed for the stations' location have been examined, including the distance from the existing fire station. S the distance from the areas at risk of earthquakes, the high population density, the density of wooden buildings, the proximity to the roads—the main and density of hazardous materials facilities., the data set of fire stations in Istanbul city was used, to check the results and simulation in this research. This data set contains two parts, one of which contains information about the location of the stations, which has 124 data, and the other contains related information to the areas where the fire occurred and has 107 data. In this research, five scenarios were set, the first scenario of two parameters, the second scenario of three parameters, the third, fourth, and fifth scenarios of four parameters and their influence on the choice of the parent were investigated, and the results showed that the best solution is It is obtained that both goals have the same weight in the scenarios. It happens when the number of stations reaches the desired level. In fact, by increasing the number of stations to the appropriate size, the urban coverage amount reached the desired results.