Dynamic Sweep: A Hierarchical Framework for Emergency Rescue

Abstract

In the critical domain of emergency response, rapid building evacuation and rescue are often hindered by complex layouts and dynamic hazards such as fire spread, toxic smoke, structural instability, and unpredictable occupant behaviour. To address the challenge of optimizing rescue sweep strategies, this paper establishes a comprehensive mathematical framework that transitions from traditional static planning to dynamic, adaptive decision-making, with the objectives of minimizing rescue completion time and maximizing occupant safety under uncertain conditions. First, a three-level evaluation system based on the AHP–Entropy Weight Method is constructed to quantify 32 critical influence factors, ranging from environmental conditions and building layout to occupant behaviour and technical support. The resulting weighted framework provides a data-driven foundation for subsequent optimization models. Three representative building configurations are then examined. For a 1D linear layout, a Divide-and-Conquer strategy reduces completion time by 42% compared with a single-entry approach. For a 2D branching layout, the rescue problem is formulated as a load-balanced Multi-Agent Traveling Salesman Problem (MA-TSP). For a 3D high-rise structure, a hierarchical Pincer Strategy is developed by nesting the MA-TSP within a multi-objective vehicle-routing framework and strategically leveraging vertical assets such as fire-service elevators. Finally, a Dynamic Adaptive Replanning Model is introduced using time-dependent hazard functions, dynamic edge costs, and occupant re-entry events. A Rolling-Horizon Replanning mechanism continuously updates rescue routes as the emergency evolves.