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3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。
In view of the fire emergency evacuation problem of large space buildings,in case of fire,provide a shortest safety route from dangerous area to safe area for evacuees.In this paper,the fire evacuation path planning method based on quantum ant colony optimization is adopted.The pheromone is represented by quantum bits,and the pheromone is updated by quantum revolving door feedback control.It can not only reflect the efficiency of quantum parallel computing,but also have the better optimization ability of ant colony algorithm.By comparing the three benchmark function optimization simulation with the traditional quantum evolution algorithm,the performance of the algorithm is proved to be better.The simulation results show that the algorithm can effectively avoid falling into local optimum and has faster convergence speed than ant colony algorithm,and is more effective in evacuation path planning.
作者
王钾
王慧琴
冯路佳
Wang Jia;Wang Huiqin;Feng Lujia(School of Information and Control Engineering,Xi'an University of Architecture and Technology,Xi'an 710054,China)
出处
《计算机测量与控制》
2020年第7期167-172,共6页
Computer Measurement &Control
基金
陕西省教育厅重点科学研究计划(Z20180411)
陕西省文物局项目(Z20180301)
西安市社会科学规划基金项目(Z20190065)。
关键词
消防疏散
路径规划
量子蚁群算法
量子比特
量子旋转门
fire evacuation
path planning
quantum ant colony algorithm
qubit
Quantum revolving gate
