Planning and Research of Spatial Emergency Evacuation Path Based on the Fusion of Ant Colony and Genetic Algorithm

The application of the ant colony algorithm and genetic algorithm to the path optimization problem of fire evacuation on large floors is the hottest research direction of ant colony algorithm and genetic algorithm, which needs to be innovated and researched on the improvement and integration of algorithms, analyze the influencing factors of modern building fire evacuation from a global perspective, and realize the dynamic path optimization of fire evacuation path. To address the challenges of insufficient initial pheromones, slow path generation, and local optima in traditional ant colony and genetic algorithms for fire environment path planning, this paper introduces a hybrid approach that combines ant colony and genetic algorithms. The proposed fusion algorithm aims to reduce the number of iterations, accelerate path generation, and ultimately achieve optimal solutions in path planning. Not only in the two-dimensional plane can the fire escape path be generated, but also in the three-dimensional space, the generation of an escape path can be achieved, and it can be realized on the second, third, and multi-layer floors. As the initial best path of the ant colony algorithm, the pheromone update approach of the MAX-MIN Ant System is refined. This improvement not only preserves the benefits of updating the overall best path but also incorporates updates to the optimal path at the current iteration.This study offers valuable insights and verifies its findings through simulation, thereby providing useful guidance for the planning process and research of spatial dynamic emergency evacuation path based on the fusion of ant colony and genetic algorithm.