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Applied Artificial Bee Colony Optimization Algorithm in Fire Evacuation Routing System

Every minute counts in an event of fire evacuation where evacuees need to make immediate routing decisions in a condition of low visibility, low environmental familiarity, and high anxiety. However, the existing fire evacuation routing models using various algorithm such as ant colony optimization o...

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Main Authors: Wang, Chen, Wood, Lincoln Christopher, Li, Heng, Aw, Zhenye, Keshavarzsaleh, Abolfazl
Format: Article
Published: Hindawi Publishing Corporation 2018
Subjects:
TH Building construction
Online Access:http://eprints.um.edu.my/20402/
https://doi.org/10.1155/2018/7962952
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spelling my.um.eprints.204022019-02-19T08:14:19Z http://eprints.um.edu.my/20402/ Applied Artificial Bee Colony Optimization Algorithm in Fire Evacuation Routing System Wang, Chen Wood, Lincoln Christopher Li, Heng Aw, Zhenye Keshavarzsaleh, Abolfazl TH Building construction Every minute counts in an event of fire evacuation where evacuees need to make immediate routing decisions in a condition of low visibility, low environmental familiarity, and high anxiety. However, the existing fire evacuation routing models using various algorithm such as ant colony optimization or particle swarm optimization can neither properly interpret the delay caused by congestion during evacuation nor determine the best layout of emergency exit guidance signs; thus bee colony optimization is expected to solve the problem. This study aims to develop a fire evacuation routing model "Bee-Fire" using artificial bee colony optimization (BCO) and to test the routing model through a simulation run. Bee-Fire is able to find the optimal fire evacuation routing solutions; thus not only the clearance time but also the total evacuation time can be reduced. Simulation shows that Bee-Fire could save 10.12% clearance time and 15.41% total evacuation time; thus the congestion during the evacuation process could be effectively avoided and thus the evacuation becomes more systematic and efficient. Hindawi Publishing Corporation 2018 Article PeerReviewed Wang, Chen and Wood, Lincoln Christopher and Li, Heng and Aw, Zhenye and Keshavarzsaleh, Abolfazl (2018) Applied Artificial Bee Colony Optimization Algorithm in Fire Evacuation Routing System. Journal of Applied Mathematics, 2018. pp. 1-17. ISSN 1110-757X https://doi.org/10.1155/2018/7962952 doi:10.1155/2018/7962952
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic TH Building construction
spellingShingle TH Building construction
Wang, Chen
Wood, Lincoln Christopher
Li, Heng
Aw, Zhenye
Keshavarzsaleh, Abolfazl
Applied Artificial Bee Colony Optimization Algorithm in Fire Evacuation Routing System
description Every minute counts in an event of fire evacuation where evacuees need to make immediate routing decisions in a condition of low visibility, low environmental familiarity, and high anxiety. However, the existing fire evacuation routing models using various algorithm such as ant colony optimization or particle swarm optimization can neither properly interpret the delay caused by congestion during evacuation nor determine the best layout of emergency exit guidance signs; thus bee colony optimization is expected to solve the problem. This study aims to develop a fire evacuation routing model "Bee-Fire" using artificial bee colony optimization (BCO) and to test the routing model through a simulation run. Bee-Fire is able to find the optimal fire evacuation routing solutions; thus not only the clearance time but also the total evacuation time can be reduced. Simulation shows that Bee-Fire could save 10.12% clearance time and 15.41% total evacuation time; thus the congestion during the evacuation process could be effectively avoided and thus the evacuation becomes more systematic and efficient.
format Article
author Wang, Chen
Wood, Lincoln Christopher
Li, Heng
Aw, Zhenye
Keshavarzsaleh, Abolfazl
author_facet Wang, Chen
Wood, Lincoln Christopher
Li, Heng
Aw, Zhenye
Keshavarzsaleh, Abolfazl
author_sort Wang, Chen
title Applied Artificial Bee Colony Optimization Algorithm in Fire Evacuation Routing System
title_short Applied Artificial Bee Colony Optimization Algorithm in Fire Evacuation Routing System
title_full Applied Artificial Bee Colony Optimization Algorithm in Fire Evacuation Routing System
title_fullStr Applied Artificial Bee Colony Optimization Algorithm in Fire Evacuation Routing System
title_full_unstemmed Applied Artificial Bee Colony Optimization Algorithm in Fire Evacuation Routing System
title_sort applied artificial bee colony optimization algorithm in fire evacuation routing system
publisher Hindawi Publishing Corporation
publishDate 2018
url http://eprints.um.edu.my/20402/
https://doi.org/10.1155/2018/7962952
_version_ 1643691267976069120
score 13.211869

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