摘要
针对粒子群优化算法(PSO)在疏散模拟中局部寻优能力差、易过早收敛的问题,提出了一种基于改进PSO算法的人群疏散模型。在原有模型基础上引入正向驱动力、排斥驱动力、疏散人员的恐慌程度等因子;根据环境因素和人群移动动态调整疏散人员的方向,并在最佳出口选择机制下趋向理想出口;对出口位置等物理因素进行疏散效率的参数化仿真实验。实验结果表明了疏散模型的有效性,可有效避免疏散过程中的局部拥堵现象,从而为建筑设计与管理人员提供合理参考。
Aiming at the poor local optimization ability and easy premature convergence of the particle swarm optimization(PSO)algorithm in evacuation simulation,a crowd evacuation model based on the improved PSO algorithm is proposed.On the basis of the original model,factors such as the forward driving force,exclusion driving force and panic degree of evacuees are introduced.According to the environmental factors and crowd movement,evacuees'direction is dynamically adjusted,and tends to the ideal exit under the optimal exit selection mechanism.The parametric simulation experiment of evacuation efficiency is carried out for the physical factors such as the exit location.The experimental results show that the evacuation model is effective,and can avoid local congestion,provides reasonable reference to the architectural design and management.
作者
李昌华
毕成功
李智杰
Li Changhua;Bi Chenggong;Li Zhijie(School of Information and Control Engineering,Xi'an University of Architecture and Technology,Xi'an 710055,China)
出处
《系统仿真学报》
CAS
CSCD
北大核心
2020年第6期1000-1008,共9页
Journal of System Simulation
基金
国家自然科学基金(61373112)
陕西省自然科学基金(2016JM6078)。
关键词
疏散模拟
PSO算法
驱动力
恐慌程度
出口选择
evacuation simulation
PSO algorithm
driving force
panic level
export choice
