基于人工蜂群算法的室内紧急疏散模型

Xinlu Zong, Jiayuan Du, Wei Liu, Lu Zhang, Qian Huang
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引用次数: 2

摘要

为了快速高效地模拟疏散场景下人群的运动过程,以减少紧急疏散中的人员伤亡,本文提出了一种基于改进人工群算法的室内紧急疏散模型。本文采用元胞自动机(CA)模型建立疏散环境,然后采用人工蜂群(ABC)算法对人群疏散进行模拟。然而,由于某个位置的相邻细胞中存在太多障碍,该位置的个体不得不等待。如果使用距离方程来计算适应度,可能会导致其他个体选择这些位置作为新位置,重复上述错误。为了减少这种情况的发生,我们改进了ABC算法的适应度函数。在适应度函数中,引入了社会力模型中的吸引力和排斥力因素。并在ABC算法的基础上,提出了视觉雇佣蜂。视觉被雇佣蜂引导旁观蜂疏散,提高疏散效率。本文的研究成果可以为疏散建模提供思路,并为制定疏散策略提供有益的指导,以减少疏散时间和灾害损失。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Indoor Emergency Evacuation Model Based on Artificial Bee Colony Algorithm
In order to quickly and efficiently simulate the crowd movement process under the evacuation scene, so as to reduce the casualties in emergency evacuation, this article proposes an indoor emergency evacuation model based on the improved artificial swarm algorithm. In this article, the cellular automata (CA) model is used to establish the evacuation environment, and then the artificial bee colony (ABC) algorithm is used to simulate the crowd evacuation. However, due to too many obstacles existing in the neighboring cells of some position, the individual in that position have to wait. If the distance equation is used to calculate the fitness, it may cause other individuals to choose these positions as new position and repeat the same mistake above. To reduce the occurrence of such cases, we improve the fitness function of the ABC algorithm. In the fitness function, the factors of attraction and repulsion force in social force model are introduced. And on the basis of the ABC algorithm, we propose the visual employed bee. The visual employed bee leads the onlooker bee to evacuate, so as to improve the efficiency of evacuation. The research results of this article can provide ideas for evacuation modeling and useful guidance for formulating evacuation strategies to reduce evacuation time and disaster losses.
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