基于智能粒子群优化算法的人员疏散问题研究  

People’s Evacuating Research Based on Intelligent Particle Swarm Optimization Algorithm

作　　者：任子晖[1] 王坚[1] 

机构地区：[1]同济大学CIMS中心,上海201804

出　　处：《系统仿真学报》2010年第12期2847-2852,2881,共7页Journal of System Simulation

基　　金：国家科技支撑计划项目(2006BAG01A02)(2006BAF01A46);上海市科技发展基金项目(08201201905)(08DZ1120802)

摘　　要：针对建筑物内发生火灾时人员疏散的逃逸行为进行了研究,将智能粒子群优化算法应用在人员逃逸的过程中,提出了一种智能粒子群逃逸模型。将行人群比拟为粒子群,并将粒子赋予一定的维能力,此时的智能粒子将会具有类似行人的一些特征如行为特征和心理特征。智能粒子在受灾害模型与自身思维特征模型的影响下,确定其逃逸的速度包括速度的大小和方向,然后改变自己目前的位置。在建模的过程中,还考虑了智能粒子间的碰撞及建筑物内诱导信息的作用。最后通过应用智能粒子群优化算法对某一建筑物内发生火灾时人员逃逸行为的二维仿真实验来验证模型的有效性及算法的可行性。The escape behavior of people’s evacuating in the fire disaster was researched.The Intelligent Particle Swarm Optimization （IPSO） was applied in the processing of escaping.A novel IPSO escape model was proposed.The pedestrians were assimilated as the particles.All particles were endowed with thoughts like human being.These intelligent particles will have some characteristic such as behavior and psychology characteristic at present.Their velocity included the direction and the magnitude under the influence of the disaster model and thinking characteristic model was determined.Then the particles positions were changed.The collision of particles and the effect of elicitation information in building were also considered.Most importantly,the simulated results demonstrate that method is feasible and efficient to simulate the escape behavior in fire disaster,especially to drilling.

关 键 词：智能粒子群优化 建筑物火灾 逃逸行为 灾害模型 思维特征模型 碰撞 仿真 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]