李欣妍,
魏晓鸽,
李森,
黄梦溪,
李栋禄
郑州轻工业大学建筑环境工程学院 郑州 450000
基金项目:河南省科技攻关项目“高层住宅建筑家庭集聚疏散行为的实验与模拟研究”(172102310670)
详细信息
作者简介:曹祥红：女，1972年生，副教授，研究方向为建筑电气节能技术、智能照明控制技术、智能供配电技术
李欣妍：女，1994年生，硕士生，研究方向为智能照明控制技术
魏晓鸽：女，1987年生，讲师，研究方向为建筑科学与工程、安全科学与灾害防治
李森：男，1987年生，讲师，研究方向为建筑科学与工程、安全科学与灾害防治
黄梦溪：女，1995年生，硕士生，研究方向为建筑电气节能技术
李栋禄：男，1994年生，硕士生，研究方向为智能供配电技术
通讯作者:曹祥红 caoxhong@zzuli.edu.cn
中图分类号:TP312计量
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被引次数:0
出版历程
收稿日期:2019-11-01
修回日期:2020-05-08
网络出版日期:2020-05-17
刊出日期:2020-06-22
Dynamic Programming of Emergency Evacuation Path Based on Dijkstra-ACO Hybrid Algorithm
Xianghong CAO,,Xinyan LI,
Xiaoge WEI,
Sen LI,
Mengxi HUANG,
Donglu LI
School of Building Environmental Engineering, Zhengzhou University of Light Industry, Zhengzhou 450000, China
Funds:The Science and Technology in Henan Province Project “An Experimental and Simulated Study on Family Agglomeration and Evacuation Behavior in High-rise Residential Buildings” (172102310670)
摘要
摘要:现代建筑设计趋于多样化，内部结构和功能越来越复杂，而传统疏散系统逃生指示方向固定、人员疏散时间较长，火灾发生时，不能够及时改变指示方向，易将逃生人员导向危险区域，威胁被困人员生命安全。该文提出了一种Dijkstra-ACO混合路径动态规划算法，在Dijkstra算法获得全局最优路径的基础上再采用蚁群优化(ACO)算法对每个节点进一步优化以获取最优路径，并节省算法运行时间。通过实验仿真验证了混合算法的有效性，能够根据起火点动态规划疏散路径，及时调整疏散指示方向，为火场中人员疏散逃生赢得宝贵时间。
关键词:应急疏散路径/
动态规划/
Dijkstra算法/
蚁群优化算法
Abstract:With an increasing diversity in modern architectural design, the inner structure of buildings is much more complex than before, which makes the traditional fire emergency escape indication system fail to provide people with real-time instructions because of its inflexibility of changing direction. These failures always lead people to dangerous areas during a fire emergency, which is actual a threaten to people in buildings. A combined algorithm to find a path dynamically during a fire emergency based on Dijkstra and Ant Colony Optimization (ACO) algorithm is presented in this article. This new algorithm shortens the programming time by getting a globally optimal path based on Dijkstra algorithm and operates every single point with ACO algorithm in sequence to get a best path. The combined algorithm is tested by a simulation, in which it is proved effective in adjusting evacuation path depending on the point of ignition. The changeable real-time indication will extend the escaping time with people in a burning building, which is quite precious for saving lives.
Key words:Emergency evacuation path/
Dynamic programming/
Dijkstra algorithm/
Ant Colony Optimization (ACO) algorithm
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