An Optimization Method for Evacuation Guidance in Multi-Room Scenarios

In emergency situations, individuals often experience panic and may struggle to find their way to safety. In such cases, the presence of trained leaders is crucial to provide guidance for evacuation and ensure the safety of those evacuating. However, determining the optimal positions of leaders in complex environments to guide the maximum number of pedestrians presents a significant challenge. To address this problem, we propose an Entropy-Based Maximum Coverage Model(EMCM) to enhance evacuation guidance. Initially, we employ the social force model to describe pedestrian movement characteristics, while the environmental features of the evacuation area are delineated using a navigation network. Subsequently, we introduce an urgency model grounded in evacuation entropy to quantify the urgency experienced by pedestrians. Thirdly, we frame the problem of leader positioning as an optimization challenge focused on maximizing entropy coverage, thereby increasing the number of individuals a leader can effectively guide. Finally, we employ AnyLogic to construct simulation scenarios that visualize the leadership process. This innovative method holds the potential to offer valuable support in the formulation of effective evacuation strategies during emergency situations.