Integrated PTS fire evacuation path planning algorithm

Abstract

Fire evacuation in large-scale buildings presents significant challenges, including prolonged evacuation times, exit congestion, and frequent communication breakdowns. To address these issues, this study proposes a novel hybrid fire evacuation path-planning algorithm that integrates the Pathfinder Algorithm (PFA) with the Tunicate Swarm Algorithm (TSA). This approach transforms the evacuation task into a sequence optimization problem, leveraging bio-inspired heuristics to enhance both safety and efficiency. The research introduces an innovative solution by integrating an IoT-enabled, cloud-based architecture supported by UAV relays, ensuring robust communication and minimizing on-site computational latency. Additionally, the development of an optimized environmental heuristic function allows the algorithm to dynamically adapt to hazardous conditions, reducing potential casualties and mitigating congestion. Experimental results across various grid configurations demonstrate significant advantages, achieving a 7.7% reduction in evacuation time and improving robustness in dynamic fire scenarios. These findings underscore the effectiveness and scalability of the PFA-TSA algorithm, positioning it as a superior solution for addressing the complexities of fire evacuation planning and advancing intelligent emergency response systems.