An Optimization Model for Evacuation Based on Cellular Automata and Ant Colony Algorithm

With the progress of construction technology, the modern buildings become more and more complicated and large-sized. It is difficult to avoid sudden and catastrophic emergency events for interior buildings. Hence, it is very important to establish an evacuation model to simulate evacuation behavior of pedestrians under real condition and make a scientific and effective evacuation plan. For handling with the problems of emergency evacuation path in buildings, an improved cellular automata model based on ant colony optimization algorithm (ACO) is proposed. The proposed model considers the neighbors moving rules of cellular automata and law of export selection rule is used as heuristic information of ant colony optimization algorithm, it reflects the behavior of personnel path choice more really. Finally, the model has been applied to simulate the whole evacuation process in a classroom. By simulating the process of pedestrian evacuation with the model, the results show that the proposed model could achieve shorter evacuation time than basic ACO, it's feasible for solving evacuation planning problem.