Research On Emergency Medical Supplies Allocation And Vehicle Routing Problem Under The Background Of Epidemic

In recent years,public health emergencies such as epidemics have occurred more frequently,such as: SARS in 2003,influenza H1N1 in 2009,and COVID-19 in 2020.These sudden epidemics are highly contagious,causing serious damage to people’s health.In order to alleviate the harm caused by these epidemics and restrain the spread of the epidemic,it is necessary to actively carry out emergency rescue work and provide a large number of emergency medical supplies to the affected areas.However,in the early stage of rescue,the quantity of emergency medical supplies is limited,and the urgency of infected areas is different.How to allocate emergency medical supplies fairly and reasonably and deliver them to each material demand point has become an important issue for decision makers to think about.Therefore,in the context of public health emergencies such as epidemics,this paper mainly studies the allocation of emergency medical supplies and vehicle routing planning.The specific research contents are as follows:(1)Correlative theory review.On the basis of the explanation of the concept,characteristics and classification of emergency medical supplies,the characteristics and principles of emergency medical supplies allocation under the epidemic background were clarified,and the relevant algorithms for solving the allocation model were sorted out.At the same time,the concept and classification of vehicle routing problem are summarized.On this basis,the vehicle routing problem of emergency medical supplies under the background of epidemic situation is compared with ordinary vehicle routing problem,its characteristics are clarified,and targeted improvements are made.Finally,the relevant algorithms for solving the vehicle routing problem of emergency medical supplies are summarized.(2)Analysis of service urgency.First of all,based on the background of the epidemic,the factors that affect the service urgency of material demand points were classified and sorted,and the corresponding evaluation index system was constructed.Secondly,the features of the commonly used evaluation methods were analyzed.Combined with the characteristics of the epidemic,the B-type correlation degree was introduced into the TOPSIS method for improvement.When determining the weight,entropy value method combined with AHP method was adopted to give weight,and the whole evaluation process was sorted out.Finally,17 prefecture-level cities affected by COVID-19 in Hubei Province were taken as the material demand points for example analysis,and the service urgency of each demand point was obtained.The results were compared with those obtained by directly applying TOPSIS method.(3)Formulation of allocation plan.In the case that emergency medical supplies are in short supply in the early stage of emergency rescue,the multi-emergency distribution center and multi-material demand point are taken as the research object,and the service urgency of each demand point is applied to the model construction,so as to establish a multi-objective emergency medical supplies allocation model that takes into account timeliness and fairness.Finally,taking the COVID-19 outbreak in Hubei Province as an example,the NSGA-Ⅱ algorithm was used to solve the problem,and each allocation plan was analyzed from the perspective of decision-makers.Meanwhile,the material reserves of the emergency distribution center were taken as variables for sensitivity analysis.(4)Optimization of vehicle routing.Based on the determination of the emergency medical supplies allocation plan,the practical allocation quantity is taken as the demand,and combined with the distinguishing features of the epidemic of this kind of public health emergencies,the composition of the total distribution cost is correspondingly improved:the driving cost is measured by the time factor,and the number of vehicles is measured with fixed costs,increased penalty costs,and government subsidies,a vehicle routing optimization model for emergency medical supplies that considers service urgency is finally established.The selected example is solved by genetic algorithm,and the optimization results are compared with those without considering service urgency.There are 25 figures,26 tables and 72 references in this paper.