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

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 exi...

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Main Authors: Khamis, N., Selamat, H., Ismail, F. S., Lutfy, O. F., Haniff, M. F., Nordin, I. N. A. M.
Format: Article
Published: Elsevier Ltd. 2020
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Online Access:http://eprints.utm.my/id/eprint/87465/
http://www.dx.doi.org/ 10.1016/j.chaos.2019.109505
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spelling my.utm.874652020-11-08T04:00:09Z http://eprints.utm.my/id/eprint/87465/ Optimized exit door locations for a safer emergency evacuation using crowd evacuation model and artificial bee colony optimization Khamis, N. Selamat, H. Ismail, F. S. Lutfy, O. F. Haniff, M. F. Nordin, I. N. A. M. T Technology (General) 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. Elsevier Ltd. 2020-02 Article PeerReviewed Khamis, N. and Selamat, H. and Ismail, F. S. and Lutfy, O. F. and Haniff, M. F. and Nordin, I. N. A. M. (2020) Optimized exit door locations for a safer emergency evacuation using crowd evacuation model and artificial bee colony optimization. Chaos, Solitons and Fractals, 131 . ISSN 0960-0779 http://www.dx.doi.org/ 10.1016/j.chaos.2019.109505 DOI: 10.1016/j.chaos.2019.109505
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic T Technology (General)
spellingShingle T Technology (General)
Khamis, N.
Selamat, H.
Ismail, F. S.
Lutfy, O. F.
Haniff, M. F.
Nordin, I. N. A. M.
Optimized exit door locations for a safer emergency evacuation using crowd evacuation model and artificial bee colony optimization
description 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.
format Article
author Khamis, N.
Selamat, H.
Ismail, F. S.
Lutfy, O. F.
Haniff, M. F.
Nordin, I. N. A. M.
author_facet Khamis, N.
Selamat, H.
Ismail, F. S.
Lutfy, O. F.
Haniff, M. F.
Nordin, I. N. A. M.
author_sort Khamis, N.
title Optimized exit door locations for a safer emergency evacuation using crowd evacuation model and artificial bee colony optimization
title_short Optimized exit door locations for a safer emergency evacuation using crowd evacuation model and artificial bee colony optimization
title_full Optimized exit door locations for a safer emergency evacuation using crowd evacuation model and artificial bee colony optimization
title_fullStr Optimized exit door locations for a safer emergency evacuation using crowd evacuation model and artificial bee colony optimization
title_full_unstemmed Optimized exit door locations for a safer emergency evacuation using crowd evacuation model and artificial bee colony optimization
title_sort optimized exit door locations for a safer emergency evacuation using crowd evacuation model and artificial bee colony optimization
publisher Elsevier Ltd.
publishDate 2020
url http://eprints.utm.my/id/eprint/87465/
http://www.dx.doi.org/ 10.1016/j.chaos.2019.109505
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