基于量子蚁群算法的建筑消防疏散路径规划

Building fire evacuation path planning based on quantum ant colony algorithm

摘要:

摘要：针对现在大空间建筑消防应急疏散问题，在火灾发生时，为撤离人群提供一条从危险区域到安全地带的最短安全路线。对疏散路径优化进行了研究，提出一种融合量子进化算法的改进蚁群算法用于消防疏散路径规划，用量子比特表示信息素，量子旋转门反馈控制信息素更新，即能体现量子并行计算的高效性，又能拥有蚁群算法较好的寻优能力。通过三个基准函数优化仿真与传统量子进化算法进行对比，证明算法较优的性能。再通过路径优化的仿真实验与经典蚁群算法进行比较，结果表明，算法能够有效避免陷入局部最优和拥有更快的收敛速度，在疏散路径规划中更为有效。

Abstract:

Aiming at the fire emergency evacuation of large space buildings, the shortest safe route from dangerous area to safety zone is provided for evacuees when fire happens.An improved ant colony algorithm based on quantum evolutionary algorithm (QEA) is proposed for fire evacuation path planning The pheromone is represented by quantum bits, and the pheromone is updated by quantum revolving gate feedback, which shows the high efficiency of quantum parallel computing and has better optimization ability of ant colony algorithm.Compared with the traditional quantum evolutionary algorithm, three benchmark function optimization simulation shows that the algorithm has better performance.Compared with the classical ant colony algorithm, the simulation results show that the algorithm can avoid local optimization and has faster convergence speed, and is more effective in evacuation path planning.