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Optimized exit door locations for a safer emergency evacuation using crowd evacuation model and artificial bee colony optimization

Authors :
Omar Farouq Lutfy
Ili Najaa Aimi Mohd Nordin
Hazlina Selamat
Mohamad Fadzli Haniff
Nurulaqilla Khamis
Fatimah Sham Ismail
Source :
Chaos, Solitons & Fractals. 131:109505
Publication Year :
2020
Publisher :
Elsevier BV, 2020.

Abstract

Overcrowding during emergency evacuation can cause crowd stampede and trampling that will lead to serious injuries or fatalities. These situations are likely to occur in natural or man-made disasters in open or closed spaces. The inefficient building design such as the unsuitable placement of an exit door is one of the key factors that contribute to the above tragedies. Most existing works used a trial and error method for a single room scenario in finding optimal locations of the exit doors. The main limitation in these works is that it is not suitable for handling multi-room problems and more complex room arrangements, since such problems would require a tedious process. To overcome this limitation, Artificial Bee Colony (ABC) optimization algorithm based on stochastic method is proposed in this paper. Compared to other optimization techniques, this algorithm requires less control parameters to be tuned in finding the most optimal exit door locations. A crowd evacuation model based on the Social Force Model (SFM) is used in representing the crowd dynamics and becomes the basis for the cost functions for the optimizer. The presented methodology has shown that the optimum locations of exit doors for a multi-room scenario can improve the evacuation efficiency; by minimizing crowd evacuation times and maximizing the number of people being evacuated. It is also clearly demonstrated that the optimized design is remarkable in improving the evacuation efficiency under different desired speed of crowd to evacuate.

Details

ISSN :
09600779
Volume :
131
Database :
OpenAIRE
Journal :
Chaos, Solitons & Fractals
Accession number :
edsair.doi...........12cd82b5a82a80b7f75f7ba1ec2b85fa
Full Text :
https://doi.org/10.1016/j.chaos.2019.109505