Citation

Jun XU, Xiao LI, Xiulai W. China Saf. Sci. J. 2023; 33(11): 156-164.

Copyright

(Copyright © 2023, China Occupational Safety and Health Association, Publisher Gai Xue bao)

DOI

10.16265/j.cnki.issn1003-3033.2023.11.1061

PMID

unavailable

Abstract

In order to improve the joint emergency rescue efficiency of rescue forces under different emergency scenarios, and to reduce rescue risk and property losses, a scenario analysis method was used to estimate the parameters of emergency state uncertainty, and an integrated emergency vehicle scheduling model aimed at minimizing the total scheduling cost and risk was established by introducing risk aversion level. Secondly, Non-dominated Sorting Genetic Algorithms(NSGA-II) was used to solve the objective function value, and the simulation case was used to compare and analyze the solution results under the consideration of the scenario and without consideration of the scenario. Finally, the relationship between penalty cost and risk aversion level in different scenarios was analyzed, the reasonable risk aversion level value was given, and the final scheduling scheme was selected. The results show that the model and scheme can effectively meet the needs of different emergency situations, improve rescue efficiency, and solve the comprehensive scheduling problem of emergency vehicles under the combined effects of scenarios and risk.

Key words: emergency rescue, scenario analysis, scheduling scheme, risk aversion level, rescue efficiency

Language: en