In order to improve the efficiency of rescue and evacuation of the people trapped in the subway station in severe rainstorms,an optimization model and solution approach for subway personnel's emergency rescue and evacuation is developed,which decides the facility location,emergency route and flow allocation simultaneously.Considering the rainstorms'severity and the psychological panic of trapped people during emergency rescue,an improved perceived risk assessment is designed.Then,addressing the framework of multi-stage emergency rescue and evacuation system,a location-routing model,minimizing the total cost and perceived risk,is developed for the subways emergency rescue and evacuation.The two-stage solution approach based on decomposition techniques using multi-objective evolutionary and branch and cut algorithms is designed.Finally,a case study of Zhengzhou and several tests are provided to evaluate the effectiveness.The computational results show that,new model and algorithm can provide an efficient plan within 2.13 seconds,and has certain sensitivity to key parameters.Comparing to the traditional model,the new risk assessment can reduce the transportation cost by 9.03%.Comparing to the general multi-objective optimization methods,the new algorithm can reduce the calculation time by at least 60.00%,and keeps stable performance in solving problems of different scales.
维普
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