An Optimization Method for Dynamic Evacuation Route Programming Based on Improved Ant Colony Algorithm

Improved Ant colony algorithm is applied to the dynamic evacuation route optimization (DERO) in this paper. The traditional ant colony algorithm is improved in term of the Tabu list and searching termination condition to simulate the process of human evacuation within a building. The route with the lowest risk is identified by risk analysis according to environmental changes. The method has significance meanings for improving the efficiency of the escape system and reducing casualties caused by a fire. The simulations of different size of evacuation scenarios show that the improved algorithm is effective to solve the problem of dynamic evacuation route optimization.