基于改进蚁群算法的建筑火灾疏散路径规划研究

doi:10.16182/j.issn1004731x.joss.20-0978

系统仿真学报 ›› 2022, Vol. 34 ›› Issue (5): 1044-1053.doi: 10.16182/j.issn1004731x.joss.20-0978

基于改进蚁群算法的建筑火灾疏散路径规划研究

梁江涛(), 王慧琴()

西安建筑科技大学　信息与控制工程学院，陕西　西安　710055

收稿日期:2020-12-07 修回日期:2021-02-11 出版日期:2022-05-18 发布日期:2022-05-25
通讯作者: 王慧琴 E-mail:893074028@qq.com;hqwang@xauat.edu.cn
作者简介:梁江涛（1995-），男，硕士生，研究方向为智能建筑。E-mail：893074028@qq.com
基金资助:
陕西省教育厅重点科学研究计划(Z20180411)

Study on Building Fire Evacuation Path Planning Based on Improved Ant Colony Algorithm

Jiangtao Liang(), Huiqin Wang()

School of Information and Control Engineering, Xi’an University of Architecture and Technology, Xi’an 710055, China

Received:2020-12-07 Revised:2021-02-11 Online:2022-05-18 Published:2022-05-25
Contact: Huiqin Wang E-mail:893074028@qq.com;hqwang@xauat.edu.cn

摘要/Abstract

摘要：

针对综合建筑火灾中人员疏散路径动态规划问题，以待疏散人员所需逃生时间最短为目标，考虑火灾产物和人群密度对人员逃生速度的影响，构建基于改进蚁群算法的人员疏散路径规划模型。建立由障碍物顶点栅格构成的疏散网络数据模型，改进蚁群算法的启发函数、死锁处理策略，引入烟花算法中的爆炸算子优化蚂蚁路径，以某综合建筑为例进行仿真实验。结果表明：该模型不仅能够避免疏散路径经过危险区域，还可根据建筑环境状况和人员分布情况实时调整疏散路径，提高了人员疏散路径安全性。

关键词: 建筑火灾, 路径规划, 蚁群算法, 人员疏散, 烟花算法

Abstract:

Aiming at the problem of dynamic planning of evacuation paths in comprehensive building fires, with the shortest escape time required for evacuees as the goal, considering the impact of fire products and crowd density on the evacuation speed of personnel, an evacuation path planning model based on improved ant colony algorithm is constructed. A evacuation network data model composed of an obstacle vertex grid is established, the inspiration function of the ant colony algorithm and the deadlock processing strategy are improved, the explosion operator in the fireworks algorithm is introduced to optimize the ant path, and a comprehensive building is used as an example for simulation experiments. The results show that the model can not only avoid evacuation paths through the dangerous area, but also adjust the evacuation path according to the construction environment and personnel distribution, which improves the safety of personnel evacuation path.

Key words: building fire, path optimization, ant colony algorithm, evacuation, fireworks algorithms

中图分类号:

TP391.9

梁江涛, 王慧琴. 基于改进蚁群算法的建筑火灾疏散路径规划研究[J]. 系统仿真学报, 2022, 34(5): 1044-1053.

Jiangtao Liang, Huiqin Wang. Study on Building Fire Evacuation Path Planning Based on Improved Ant Colony Algorithm[J]. Journal of System Simulation, 2022, 34(5): 1044-1053.

图/表 8

图1

图2

表1

主要参数对最优路径的影响

参数	取值	路径长度/m
α	0.1	91.28
	0.5	90.64
	1	90.53
	1.5	90.53
$β$	0.5	91.41
	1	91.35
	5	90.53
	7	90.63
$ρ$	0.05	90.53
	0.1	90.53
	0.3	90.78
	0.5	91.15
Q	1	90.77
	5	90.53
	10	90.53
	15	90.53

表1

图3

图4

表2

图5

表3

参考文献 17

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算法	路径长度/m	收敛迭代次数	运行时间/s
文献[17]	84.53	21	13.42
本文算法	83.23	17	13.50

算法	参数	起点终点
算法	参数	(2.5,50.5) (68.5,12.5)	(2.5,10.5) (40.5,69.5)
ACS	L/m	90.60	85.88
ACS	M/只	349.00	58.00
蚁群	L/m	96.99	87.28
蚁群	M/只	267.80	43.60
改进	L/m	90.52	85.40
蚁群	M/只	8.50	15.00

基于改进蚁群算法的建筑火灾疏散路径规划研究

Study on Building Fire Evacuation Path Planning Based on Improved Ant Colony Algorithm

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