Study On The Emergency Supplies Magement Of Natural Disasters

Management of emergency supplies is a basic work of emergency management. The success of emergency supplies management is related to the disaster relief work as well as the stability and harmony of disaster victims’lives. The management of emergency supplies includes the disaster factor analysis, the demand forecasting, and the inventory and supply chain management of emergency supplies. Success of the emergency supplies management not only needs the success of these part works but also depends on their coordination. This thesis tries to analyze the emergency supplies management systematically. Methods include the model analysis, the algorithm design, and the empirical analysis. The main body of this thesis includes three parts. They are the demand influence factor analysis, the emergency supplies demand forecasting, the inventory and supply chain management of emergency supplies. The analysis is based on unexpected natural disasters.There are many factors that influence the emergency supplies’demand during the disasters. So it is important to identify the key-factor. In the demand influence factor analysis chapter, we focus on this problem. We use the Empirical Mode Decomposition (EMD) method to solve this problem, and an example of the Snow Storm in2008is analyzed based on this method. The result shows that transport influenced by the Snow Storm is the key factor to the demand of cabbage and other necessaries, so it is very important to improve the transport conditions during the Snow Storm for the material supply.The second part is demand forecasting. As the time series of commodities demand after natural disasters usually has a great deal of nonlinearity and irregularity, it has poor prediction performance of applying the traditional statistical and econometric models such as linear regression and autoregressive moving average (ARMA) to this kind of data. This paper tries to apply a hybrid forecasting method which is an integration of empirical mode decomposition (EMD) and autoregressive integrated moving average (ARIMA). The EMD-ARIMA forecasting methodology is then applied to the prediction of agricultural products demand after the2008Chinese winter storms. Forecasting results indicate that EMD can improve the prediction accuracy of classical ARIMA forecasting method for demand of commodities after natural disasters. The third part of this thesis is inventory and supply chain management analysis. Based on a two-echelon supply chain with one manufacturer and multiple relief spots, this paper investigates the design of minimum order quantity (MOQ) contract and its impacts on the profits of supply chain members. Theoretic analyses first demonstrate that, the optimal order policy of relief spots is a piecewise function of MOQ under the MOQ contract. Numerical analyses illustrate that MOQ contract only increases the profit of the manufacturer when manufacture is the Stackelberg leader. We also analyze the demand transferring between the relief spots. We find that the demand transferring benefits all the supply chain members when the wholesale price is exogenous. But in the situation of endogenous wholesale price, demand transferring only benefits the manufacturer in most cases.