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Academic Journal of Computing & Information Science, 2019, 2(1); doi: 10.25236/AJCIS.010019.

Emergency Evacuation Model Based on Improved Adaptive ant Colony Algorithm


Qian Cheng

Corresponding Author:
Qian Cheng

School of Information Science, Beijing Language and Culture University, Beijing 100083, China


As one of the largest museums in the world, the Louvre Museum has a large number of tourists every day.Solutions to safe evacuation issues are becoming more and more needed.This paper mainly constructs a simple emergency evacuation model based on improved adaptive ant colony algorithm for the Louvre.In the process of evacuation, people can be regarded as clusters with common characteristics due to the interaction of people. This paper uses cellular automata and real-time information to determine people's evacuation behavior.The model can be used to predict and analyze the evacuation characteristics of buildings, and the results are in line with the actual situation, with good reliability and stability.


Ant colony algorithm, cellular automata, crowd evacuation

Cite This Paper

Qian Cheng, Emergency Evacuation Model Based on Improved Adaptive ant Colony Algorithm. Academic Journal of Computing & Information Science (2019) Vol. 2: 70-73. https://doi.org/10.25236/AJCIS.010019.


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