基于蚁群算法的商业步行街应急疏散决策优化  

Emergency evacuation decision optimization for commercial pedestrian streets based on ant colony algorithm

作　　者：姜雪 杨欢 张培红[1] JIANG Xue;YANG Huan;ZHANG Peihong(College of Resources and Civil Engineering,Northeastern University,Shenyang Liaoning 110819,China)

机构地区：[1]东北大学资源与土木工程学院,辽宁沈阳110819

出　　处：《中国安全科学学报》2021年第10期144-151,共8页China Safety Science Journal

基　　金：国家重点研发计划项目(2017YFC0804900)。

摘　　要：为分析基于决策优化的应急疏散方案引导下,商业步行街发生突发事件时大规模人群应急疏散的安全性,以某商业步行街为例,利用改进的自适应蚁群算法,进行疏散决策优化和疏散方案的优化设计;结合Pathfinder软件对基于优化疏散方案的人员疏散行为进行数值模拟,对比分析决策优化前后商业步行街大规模人群疏散的效率和安全性。结果表明:基于优化疏散方案对大规模人群进行疏散,在无火灾环境下疏散效率提高了8.86%;在火灾环境下疏散效率提高了6.57%。基于大规模应急疏散决策优化的应急疏散方案可有效缓解部分安全出口的人员群集滞留状况,实现应急疏散决策的全局优化。In order to analyze safety of large-scale crowd emergency evacuation under guidance of emergency evacuation plan based on decision optimization in commercial pedestrian street.Taking a commercial pedestrian street as an example,the improved adaptive ant colony algorithm was used to optimize the evacuation decision-making and the optimal design of evacuation plan.Combined with Pathfinder software,the personnel evacuation behavior based on optimized evacuation plan was simulated numerically,and the efficiency and safety of large-scale crowd evacuation in commercial pedestrian streets before and after decision optimization were compared and analyzed.The results show that the evacuation efficiency of large-scale crowd induced based on the optimized evacuation plan can be improved by 8.86%in a fire-free environment.The evacuation efficiency in the fire environment increased by 6.57%.The decision-making optimization of large-scale emergency evacuation effectively alleviates the situation of personnel cluster retention at some safety exits,the integral decision-making optimization of emergency evacuation is realized.

关 键 词：商业步行街 应急疏散 决策优化 自适应蚁群算法 Pathfinder软件 

分 类 号：X928.03[环境科学与工程—安全科学] TU998.1[建筑科学—市政工程]