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, DOI https://doi.org/10.1155/2018/7962952.
Full text not available from this repository.Abstract
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.
| Item Type: | Article |
|---|---|
| Funders: | Quanzhou Science and Technology Bureau through Research Grant no. 2018Z010 |
| Additional Information: | Zhenye Aw. Faculty of Built Environment, University of Malaya, 50603 Kuala Lumpur, Malaysia |
| Uncontrolled Keywords: | Applied Artificial Bee Colony; Optimization Algorithm; Fire Evacuation Routing System |
| Subjects: | T Technology > TH Building construction |
| Divisions: | Faculty of the Built Environment |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 19 Feb 2019 08:14 |
| Last Modified: | 19 Feb 2019 08:14 |
| URI: | http://eprints.um.edu.my/id/eprint/20402 |
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