In the context of the COVID-19 epidemic,a"double-hazard scenario"consisting of a natural disaster and a public health event simultaneously accurring is more likely to arise.However,compared with single-hazar...In the context of the COVID-19 epidemic,a"double-hazard scenario"consisting of a natural disaster and a public health event simultaneously accurring is more likely to arise.However,compared with single-hazard,multiple disasters confront the challenges of complexity,diversity,and demand urgency.To improve the efficiency of emergency material distribution under multiple disasters,this study first divided multiple disasters into three categoriles:independent scenario,sequential scenario,and coupling scenario.A set of evaluation index systems for multiple disasters was established to quantify the urgency of demand.The routing optimization model of emergency vehicles for multiple disasters was proposed by combining demand urgency and road damage,and the non-dominated sorting genetic algorithm II(NSGA-I)was used to simulate and validate the model.A coupling scenario considering two typical disasters of hurricanes and epidemics was selected as a validation example,and sensitivity analysis was also performed for different algorithms,scenarios,and constraints.The results demonstrated that the proposed model could effectively address the vehicle routing problem of emer-gency materials in the context of multiple disasters.Compared to the NSGA,the NSGA-II was used to reduce the total delivery time,cost,and penalty cost by 15.98%6,13.60%,and 16.14%,respectively.Compared with the independent scenario,the coupling scenario increased the total delivery time and cost by 186.28%and 132.48%during the epidemic.However,it reduced the total delivery time by 4.00%and increased the delivery cost by 23.55%compared with the hurricane.Compared with the model without consideration,the model considering demand urgency and road damage reduced the total delivery time and cost by 17.88%and 8.73%,respectively.The model constructed in this study addressed the vehicle routing problem considering the demand urgency and road damage in the optimization process,particularly in the context of multiple disasters.展开更多
基金funded by the Natural Science Foundation of Zhejiang Province,China(No.MS25E080023)the Natural Science Foundation of Ningbo City,China(No.2024J130)+6 种基金the Fundamental Research Funds for the Provincial Universities of Zhejiang(No.SJLY2023009)the National"111"Center on Safety and Intelligent Operation of Sea Bridge(D21013)National Natural Science Foundation of China(Nos.71971059,52262047,52302388,52272334,and 61963011)the Natural Science Foundation of Jiangsu Province,China(No.BK20230853)the Specific Research Project of Guangxi for Research Bases and Talents(No.AD20159035)the Guilin Key R&D Program[No.20210214-1]the Liuzhou Key R&D Program(No.2022AAA0103).
文摘In the context of the COVID-19 epidemic,a"double-hazard scenario"consisting of a natural disaster and a public health event simultaneously accurring is more likely to arise.However,compared with single-hazard,multiple disasters confront the challenges of complexity,diversity,and demand urgency.To improve the efficiency of emergency material distribution under multiple disasters,this study first divided multiple disasters into three categoriles:independent scenario,sequential scenario,and coupling scenario.A set of evaluation index systems for multiple disasters was established to quantify the urgency of demand.The routing optimization model of emergency vehicles for multiple disasters was proposed by combining demand urgency and road damage,and the non-dominated sorting genetic algorithm II(NSGA-I)was used to simulate and validate the model.A coupling scenario considering two typical disasters of hurricanes and epidemics was selected as a validation example,and sensitivity analysis was also performed for different algorithms,scenarios,and constraints.The results demonstrated that the proposed model could effectively address the vehicle routing problem of emer-gency materials in the context of multiple disasters.Compared to the NSGA,the NSGA-II was used to reduce the total delivery time,cost,and penalty cost by 15.98%6,13.60%,and 16.14%,respectively.Compared with the independent scenario,the coupling scenario increased the total delivery time and cost by 186.28%and 132.48%during the epidemic.However,it reduced the total delivery time by 4.00%and increased the delivery cost by 23.55%compared with the hurricane.Compared with the model without consideration,the model considering demand urgency and road damage reduced the total delivery time and cost by 17.88%and 8.73%,respectively.The model constructed in this study addressed the vehicle routing problem considering the demand urgency and road damage in the optimization process,particularly in the context of multiple disasters.
