Research on multi-objective optimization of forest fire station site selection based on improved NSGA-II

doi:10.16265/j.cnki.issn1003-3033.2026.03.1051

Abstract

Abstract:

In order to enhance the emergency response capability of the firefighting and rescue teams and the overall efficiency of the forest and grassland fire prevention and control layout, an optimization method for the site selection of forest and grassland fire stations based on hybrid fire prevention emergency roads was proposed. By combining the eight-direction tilt point algorithm with digital elevation model data, a hybrid fire emergency road network was constructed to enhance the fire brigade's early prevention and emergency response capabilities. Subsequently, the location allocation model of the improved NSGA-II was adopted to optimize the site selection of the fire station, ensuring the rational allocation of resources and expanding the coverage. The results show that the coverage rate of the hybrid fire prevention emergency road in the overall area is 96.91%, and the coverage rate in the high-risk area is 93.51%, which improves the ability of the rescue team to deal with complex terrains. The optimized layout of the fire stations has a coefficient of variation of 0.26, ensuring the inspection and response capabilities of the teams. The overall demand satisfaction rate is 0.86, ensuring that the key areas are fully protected. The optimization model proposed in this study can provide a theoretical basis for the layout of forest and grassland fire prevention and control, improve the utilization rate of rescue resources, and promote the precise development of forest fire management.

Key words: non-dominated sorting genetic algorithms II(NSGA-II), forest and grassland fires, fire station, multi-objective, site selection optimization, location allocation

CLC Number:

X928.7火灾与爆炸事故

LI Hua, CHEN Xin, YI Peng, WU Lizhou. Research on multi-objective optimization of forest fire station site selection based on improved NSGA-II[J]. China Safety Science Journal, 2026, 36(3): 171-177.

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因素	图层	要素	权重
承灾暴露程度	易燃性	NDVI	0.054 1
承载体脆弱性	脆弱性	人口密度	0.046 2
承载体脆弱性	脆弱性	重要基础设施	0.005 3
致灾危险性	水源可达性	河流湖泊	0.455 8
	交通网络可达性	道路网络	0.236 8
	森林火险气象	FFDI	0.162 6
	地形特征	高程	0.025 4
	地形特征	坡度	0.013 8