An Agent-Based Simulation of Deep Foundation Pit Emergency Evacuation Modeling in the Presence of Collapse Disaster.

With the gradual expansion of high buildings and underground spaces, deep foundation pits have been widely used in these engineering projects, but if they are not well-designed, safety problems occur. Proper deep foundation pit design requires proper exit distribution. However, calculating an adequate number of exit distributions for evaluation is difficult due to the numerous influential factors existing in the deep foundation pit environment. To this end, this paper presents a prototype of a decision-making system that uses agent-based modeling to simulate deep foundation pit evacuation in the presence of collapse disaster. By modeling the collapse occurrence process and agent escape process, an agent-based evacuation model is built, and a modified simulation-based particle swarm optimization algorithm is used to solve the optimization problem of exit distribution. Extensive experiments are conducted to verify the system, and the results show that the system provides a feasible framework for deep foundation pit evacuation.