基于改进蚁群-麻雀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-improved sparrow search algorithm

作　　者：李明海[1] 张雪婷 杨天鹏 杨一帆[1] 郭孟孟 LI Minghai;ZHANG Xueting;YANG Tianpeng;YANG Yifan;GUO Mengmeng(College of Resources Engineering,Xi'an University of Architecture and Technology,Xi'an Shaanxi 710055,China)

机构地区：[1]西安建筑科技大学资源工程学院,陕西西安710055

出　　处：《工业安全与环保》2024年第9期50-56,94,共8页Industrial Safety and Environmental Protection

摘　　要：结合改进蚁群算法(IACO)和改进麻雀搜索算法(ISSA),提出一种考虑火灾实时蔓延的动态疏散路径规划模型。采用火灾动力学软件(FDS)得到火灾环境参数,以表示火灾实时蔓延的危险程度。基于IACO强大的全局搜索能力得到初始疏散路径。采用收敛速度快的ISSA对初始路径进行优化,以提高路径的稳定性。以某综合建筑为例进行2组不同火灾环境下的仿真实验,结果表明:IACO-ISSA模型相比ACO能够根据火灾发展情况实时调整疏散路径,从而有效躲避火灾危险区域,避免了忽略火灾动态蔓延而引导疏散人员至危险区域的现象,进一步提高了疏散路径的安全性。This paper presents a dynamic evacuation path planning model to consider the real-time spread behavior of the fire combining Improved Ant Colony Algorithm(IACO)and Improved Sparrow Search Algorithm(ISSA).FDS is utilized to obtain the fire environment parameters and indicates the danger degree of real-time fire spread.The IACO is utilized to obtain the initial evacuation path due to its strong global search ability.ISSA with fast convergence speed is adopted to optimize the initial path to improve the stability of the path.Taking a comprehensive building as an example,two groups of simulation experiments in different fire environments were carried out.The results indicate the IACO-ISSA model can adjust the evacuation path according to the fire development situation to effectively avoid the fire danger area,and the phenomenon guiding evacuees to dangerous areas for ignoring the dynamic spread of fire is avoided,which further improved the safety of evacuation paths compared to ACO.

关 键 词：火灾疏散 蚁群算法 麻雀搜索算法 火灾模拟 路径规划 

分 类 号：TU998.1[建筑科学—市政工程] TP18[自动化与计算机技术—控制理论与控制工程]