TY - JOUR
T1 - Applied Artificial Bee Colony Optimization Algorithm in Fire Evacuation Routing System
AU - Wang, Chen
AU - Wood, Lincoln C.
AU - Li, Heng
AU - Aw, Zhenye
AU - Keshavarzsaleh, Abolfazl
PY - 2018/4/24
Y1 - 2018/4/24
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85046798475&partnerID=8YFLogxK
U2 - 10.1155/2018/7962952
DO - 10.1155/2018/7962952
M3 - Journal article
SN - 1110-757X
VL - 2018
JO - Journal of Applied Mathematics
JF - Journal of Applied Mathematics
M1 - 7962952
ER -