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[1]毛清华,余荣付,毛承成.基于改进蝴蝶算法和社会力模型的多出口疏散模型研究*[J].中国安全生产科学技术,2022,18(7):12-18.[doi:10.11731/j.issn.1673-193x.2022.07.002]
　MAO Qinghua,YU Rongfu,MAO Chengcheng.Research on multi-exit evacuation model based on improved butterfly algorithm and social force model[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2022,18(7):12-18.[doi:10.11731/j.issn.1673-193x.2022.07.002]
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基于改进蝴蝶算法和社会力模型的多出口疏散模型研究*
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《中国安全生产科学技术》[ISSN:1673-193X/CN:11-5335/TB]

卷:
18
期数:
2022年7期
页码:
12-18
栏目:
学术论著
出版日期:
2022-07-31

文章信息/Info

Title:
Research on multi-exit evacuation model based on improved butterfly algorithm and social force model
文章编号:
1673-193X(2022)-07-0012-07
作者:
毛清华; 余荣付; 毛承成
（1.燕山大学 经济管理学院，河北 秦皇岛 066004;
2.莫纳什大学 商学院，澳大利亚 墨尔本VIC 3145）
Author(s):
MAO Qinghua;  YU Rongfu;  MAO Chengcheng
(1.School of Economics and Management,Yanshan University,Qinhuangdao Hebei 066004,China;
2.School of Business,Monash University,Melbourne VIC 3145,Australia)
关键词:
社会力模型; 蝴蝶算法; 速度调节因子; 自适应感知概率
Keywords:
social force model;  butterfly algorithm;  speed adjustment factor;  adaptive perception probability
分类号:
X913.4
DOI:
10.11731/j.issn.1673-193x.2022.07.002
文献标志码:
A
摘要:
为提高多出口场景下行人疏散效率和精度，基于蝴蝶算法和社会力模型，提出一种新的应急疏散仿真路径规划方法。在原有社会力模型中，考虑距离出口远近及行人所处位置拥挤度对运动过程中期望速度的影响，引入速度调节因子，描述行人在疏散中的期望速度变化;针对蝴蝶算法中后期收敛速度慢和易陷入局部最优的缺陷，提出自适应感知概率参数以增强局部搜索和全局搜索之间的平衡；在每轮迭代结束时引入迭代局部搜索策略，扰动局部最优解获得中间状态，并重新搜索上述中间状态得到全局最优解。研究结果表明：提出的应急疏散仿真路径规划方法在多出口环境下能够更有效地利用出口资源，提高疏散效率。
Abstract:
In order to improve the efficiency and accuracy of pedestrian evacuation in multi-exit scenes,a new simulation path planning method of emergency evacuation was proposed based on the butterfly algorithm and social force model.In the original social force model,the influence of the distance to exit and the crowding degree of pedestrian's position on the expected speed during movement was considered,and a speed adjustment factor was introduced to describe the expected speed change of pedestrian in evacuation.Aiming at the defects of slow convergence speed and easy to fall into local optimum in the middle and late stages of butterfly algorithm,an adaptive perceptive probability parameter was proposed to enhance the balance between local search and global search.At the end of each iteration,the iterative local search strategy was introduced to obtain the intermediate state by disturbing the local optimal solution and searching the above intermediate state again to obtain the global optimal solution.The results showed that the new simulation path planning method of emergency evacuation could utilize the exit resources more effectively and improve the evacuation efficiency in multi-exit environment.

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备注/Memo

备注/Memo:
收稿日期： 2021-12-21
*基金项目： 国家自然科学基金项目(71401027)；河北省省级科技计划软科学研究专项项目(215576116D)
作者简介： 毛清华，博士，教授，主要研究方向为应急管理与共享服务资源配置与优化。
通信作者： 余荣付，硕士研究生，主要研究方向为应急管理与行人疏散。
更新日期/Last Update: 2022-08-10