Evacuation dynamic and exit optimization of a supermarket based on particle swarm optimization

被引:9
|
作者
Li, Lin [1 ]
Yu, Zhonghai [1 ]
Chen, Yang [1 ]
机构
[1] Wuhan Univ, Sch Resources & Environm Sci, Wuhan 430079, Peoples R China
关键词
Particle swarm optimization; Route calculation; Evacuation dynamic; FDS; Fire spread; PEDESTRIAN EVACUATION; MODEL; ESCAPE; CHOICE; FLOW;
D O I
10.1016/j.physa.2014.08.054
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
A modified particle swarm optimization algorithm is proposed in this paper to investigate the dynamic of pedestrian evacuation from a fire in a public building a supermarket with multiple exits and configurations of counters. Two distinctive evacuation behaviours featured by the shortest-path strategy and the following-up strategy are simulated in the model, accounting for different categories of age and sex of the pedestrians along with the impact of the fire, including gases, heat and smoke. To examine the relationship among the progress of the overall evacuation and the layout and configuration of the site, a series of simulations are conducted in various settings: without a fire and with a fire at different locations. Those experiments reveal a general pattern of two-phase evacuation, i.e., a steep section and a flat section, in addition to the impact of the presence of multiple exits on the evacuation along with the geographic locations of the exits. For the study site, our simulations indicated the deficiency of the configuration and the current layout of this site in the process of evacuation and verified the availability of proposed solutions to resolve the deficiency. More specifically, for improvement of the effectiveness of the evacuation from the site, adding an exit between Exit 6 and Exit 7 and expanding the corridor at the right side of Exit 7 would significantly reduce the evacuation time. (C) 2014 Elsevier B.V. All rights reserved.
引用
收藏
页码:157 / 172
页数:16
相关论文
共 50 条
  • [1] Multi-exit Evacuation Strategy Based on Particle Swarm Optimization with Background Field
    Zhang, Li-Jie
    Liu, Jian-Chang
    Tan, Shu-Bin
    [J]. Dongbei Daxue Xuebao/Journal of Northeastern University, 2019, 40 (09): : 1222 - 1227
  • [2] Fire Evacuation Route Determination based on Particle Swarm Optimization
    Aymaz, Seyma
    Cavdar, Tugrul
    Cavdar, Ayfer Donmez
    [J]. 2017 INTERNATIONAL ARTIFICIAL INTELLIGENCE AND DATA PROCESSING SYMPOSIUM (IDAP), 2017,
  • [3] Passengers' Evacuation in Ships Based on Neighborhood Particle Swarm Optimization
    Yuan, Gan-Nan
    Zhang, Li-Na
    Liu, Li-Qiang
    Wang, Kan
    [J]. MATHEMATICAL PROBLEMS IN ENGINEERING, 2014, 2014
  • [4] Modeling of pedestrian evacuation based on the particle swarm optimization algorithm
    Zheng, Yaochen
    Chen, Jianqiao
    Wei, Junhong
    Guo, Xiwei
    [J]. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2012, 391 (17) : 4225 - 4233
  • [5] A dynamic boundary based particle swarm optimization
    Li, Ying-Qiu
    Chi, Yu-Hong
    Wen, Tao
    [J]. Tien Tzu Hsueh Pao/Acta Electronica Sinica, 2013, 41 (05): : 865 - 870
  • [6] A particle swarm optimization based memetic algorithm for dynamic optimization problems
    Wang, Hongfeng
    Yang, Shengxiang
    Ip, W. H.
    Wang, Dingwei
    [J]. NATURAL COMPUTING, 2010, 9 (03) : 703 - 725
  • [7] Dual-archive-based particle swarm optimization for dynamic optimization
    Liu, Xiao-Fang
    Zhou, Yu-Ren
    Yu, Xue
    Lin, Ying
    [J]. APPLIED SOFT COMPUTING, 2019, 85
  • [8] A particle swarm optimization based memetic algorithm for dynamic optimization problems
    Hongfeng Wang
    Shengxiang Yang
    W. H. Ip
    Dingwei Wang
    [J]. Natural Computing, 2010, 9 : 703 - 725
  • [9] An Improved Discrete Particle Swarm Optimization in Evacuation Planning
    Yusoff, Marina
    Ariffin, Junaidah
    Mohamed, Azlinah
    [J]. 2009 INTERNATIONAL CONFERENCE OF SOFT COMPUTING AND PATTERN RECOGNITION, 2009, : 49 - +
  • [10] A dynamic chaotic mutation based particle swarm optimization for dynamic optimization of biochemical process
    Wang, Kangtai
    Li, Fupeng
    [J]. 2017 4TH INTERNATIONAL CONFERENCE ON INFORMATION SCIENCE AND CONTROL ENGINEERING (ICISCE), 2017, : 788 - 791