An optimal guidance strategy for fire evacuations: A hybrid modeling approach

Evacuation plans are subject to many restrictions in the event of a fire, and unreasonable evacuation guidance methods can affect efficiency and even cause danger. In the current study, we investigate the optimal guidance strategy for fire evacuation to obtain the optimal guider layout and the evacu...

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Vydáno v:Journal of Building Engineering Ročník 73; s. 106796
Hlavní autoři: Wang, Ke, Yuan, Weifeng, Liang, Weiqi, Yao, Yao
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Ltd 15.08.2023
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ISSN:2352-7102, 2352-7102
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Shrnutí:Evacuation plans are subject to many restrictions in the event of a fire, and unreasonable evacuation guidance methods can affect efficiency and even cause danger. In the current study, we investigate the optimal guidance strategy for fire evacuation to obtain the optimal guider layout and the evacuation paths. The environmental constraints are generated in conjunction with FDS fire simulation to transform the evacuation space into a pseudo-static obstacle grid. A multi-objective model of the guider layout is constructed, and the guider number is used as an optimization variable. The pseudo-static obstacle grid is combined with the exit fluency strategy to plan paths. The evacuation time and cost of the crowd are adopted as two objective functions. Finally, the optimal guider layout is generated by iterative optimization of NSGA-II algorithm with the introduction of a chromosome fragment deletion operator. The simulation results and comparative analysis indicate that the model can improve fire evacuation safety, enhance the utilization and balance of each exit, and reduce evacuation time and resource redundancy. •A new optimal strategy for fire evacuation with rescue guider is presented.•The optimal path is obtained based on a pseudo-static obstacle grid with an exit fluency strategy.•The guider layout is optimized based on the improved NSGA-II algorithm combined with evacuation simulation.
ISSN:2352-7102
2352-7102
DOI:10.1016/j.jobe.2023.106796