Demand Forecasting And Scheduling Optimization Of Emergency Logistics Based On Public Health Emergencies

Emergency logistics refers to a special logistics activity that provides emergency protection for the needs of material personnel funds in response to natural disasters,public health emergencies,social security incidents and other emergencies.When large-scale emergencies occur,emergency logistics becomes very important in order to ensure the safety of people’s lives and property in disaster areas and the timely supply of emergency materials.Emergency logistics is divided into natural disaster emergency logistics,emergency logistics of public health emergencies,emergency logistics for accidents and disasters,and emergency logistics of social security events.When a public health emergency occurs,the people in the place where the emergency occurs urgently need a large number of emergency supplies.If emergency supplies cannot be delivered to the site of the incident in time,people’s lives will be seriously threatened.In order to ensure the safety of people’s lives and the stable development of the country and the region,it is particularly important to establish an efficient emergency logistics system for public health emergencies.In recent years,there have been frequent public health emergencies in China,such as SARS,H1N1 influenza,H7N9 influenza,poliomyelitis,and COVID-19.In order to provide emergency logistics support in time when an event occurs,it is necessary to have accurate emergency logistics demand prediction and scientific scheduling scheme.However,there are still a series of problems to be solved in emergency logistics demand forecasting and scheduling based on public health emergencies.Therefore,considering literature review and theories on emergency logistics demand forecasting and scheduling in public health emergencies,this paper studies the demand forecasting and scheduling in emergency logistics based on public health emergencies,and uses the demand forecasting results as the data support for scheduling,which is aimed at demand forecasting and scheduling in emergency logistics scientifically and accurately to minimize the number of deaths in the incident,so as to ensure the safety of people’s lives and social stability.This paper is divided into five chapters.The first chapter is the introduction,which introduces the background and research significance of the topic.We presented a literature review from three aspects including emergency logistics,the method of emergency logistics demand forecasting,and the scheduling model of emergency logistics.Moreover,we put forward the research objectives,technical route,research methods and two points of research innovation.In the second chapter,the basic theories of emergency logistics and public health emergencies are firstly introduced.Then,three main elements of emergency logistics based on public health emergencies are summarized.Lastly,the operation links of emergency logistics are introduced,and its key problems analyzed.In the third chapter,considering the analysis of emergency logistics demand forecasting for public health emergencies,the steps and principles of emergency logistics demand forecasting are firstly described.Then,the methods of emergency logistics demand forecasting based on time series method are introduced.Lastly,the model of emergency logistics demand forecasting based on Holt linear trend method is established,and the calculation example is analyzed.In the fourth chapter,according to the optimization strategy of emergency logistics scheduling in public health emergencies,the scheduling principle and classification in emergency logistics are firstly expounded.Then,the optimization methods and scheme in emergency logistics scheduling based on integer programming method are introduced.Lastly,the scheduling model of emergency logistics aiming at minimizing the number of deaths is established,and calculation example is analyzed.The fifth chapter is the conclusion that summarizes the main research results and research shortcomings,and puts forward the future research direction from the aspects of optimizing the whole emergency logistics operation process.