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With more complex structures and denser populations, congestion is a crucial factor in estimating evacuation clearance time. This paper presents a novel evacuation model that implements a game theory combining the greatest entropy optimization criterion with stochastic Monte Carlo methods to optimize the congestion problem and other features of emergency evacuation planning. We introduce the greatest entropy criterion for convergence to Nash equilibrium in the n-person noncooperative game. The process of managing the conflict problem is divided into two steps. In the first step, we utilize Monte Carlo methods to evaluate the risk degree of each route. In the second step, we propose an improved method based on game theory, which obtains an optimal solution to guide the evacuation of all agents from the building.

A Game Theory Based on Monte Carlo Analysis for Optimizing Evacuation Routing in Complex Scenes