Details

Autor(en) / Beteiligte

• Shi, Xiuli
• Gai, Wenmei
• Xu, Ke

Titel

Bi-objective rescue path selection optimization for mine fires based on quantitative risk assessment

Ist Teil von

• Safety science, 2022-02, Vol.146, p.105492, Article 105492

Ort / Verlag

Amsterdam: Elsevier Ltd

Erscheinungsjahr

2022

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• •A dynamic bi-objective optimization model for the selection of an emergency rescue path was established.•A method for quantitatively assessing the acceptable risk level of a path is derived.•The risk of each alternative rescue path is evaluated and divided. Fires are one of the most common accidents that occur in mines, and they result in huge losses. In a mine fire accident, choosing the shortest path for rescue can speed up the rescue process and increase the success rate of saving lives. Meanwhile, ensuring the safety of rescuers is also an important factor that must be considered for effective rescue work. Only when trapped personnel and rescuers are kept safe can serious losses be avoided. Therefore, we take the shortest rescue time and the lowest danger level as optimization objectives and establish a dynamic bi-objective optimization model for the selection of an emergency rescue path. Then, a method for quantitatively assessing the acceptable risk level of a path is derived. The risk of each alternative rescue path is evaluated and divided from the two dimensions of available rescue time and acceptable danger level. Experimental results show that the shortest rescue path is not necessarily the safest. By referring to the risk assessment and zoning results of alternative rescue paths under different risk redundancy intervals, decision makers with different risk preferences can evaluate targeted rescue paths. On the basis of the results of this work, decision makers can comprehensively consider actual rescue situations and other factors in selecting optimal rescue paths. This work also maximizes the initiative of decision makers in the decision-making process.