A Study On Inventory-management For Emergency Materials Based On Fuzzy Evaluating And Grey-neural Network

The frequently happening of all sorts of " natural disaster", "man-made calamities", such as earthquake, accidents of the colliery, bird flu, calls for a large amount of emergent supplies, all-embracing to the article for daily use from dedicated device, medical equipment, communication apparatus, tackling with disaster relief, rescuing, hygiene epidemic prevention, rebuilding, order restore, etc., by which losses can be reduced and further enlargement of the disaster can be under-control, thereby there exists enormous emergent logistics demand. Only if these demands are met in the first time, with the quickest procedure and by the safest way, can the losses be minimized. So there is a high request for logistics of emergent supply.Taking emergency logistics system for enterprise's accidents as research object, coordinating with theories on modern logistics and inventory management, several critical problems, emergency logistics systems, inventory management, demand-forecasting, have been studied. The main content of this dissertation is as follows:In the first chapter, the status of relevant research in current situation has also been analyzed on the basis of literature reading, and the background, purpose and the meaning of the paper are discussed.In Chapter two, factors and specialties of emergency logistics system of enterprise are analyzed on the basis of its causes, types and main characteristics. Logistics management strategy is discussed from three aspects, purchase management; inventory management and delivery management.In Chapter three, the mode of inventory management of emergency supplies in enterprise is discussed, and the inventory management strategies for emergency logistics are set up from the aspects of classification, requirement forecasting, and stock control tactics. Moreover, a random model for inventory control is probe into.In Chapter four, the advanced classification method is discussed according to the characteristics of emergency supplies inventory. An index system for evaluating emergency supplies is put forward. A new classification management strategy of emergency supplies is studied based on fuzzy comprehensive evaluation. In Chapter five, demand prediction methods for emergency supplies are studied, in which the characteristics of randomness and fluctuation are considered. The GM(1,1) model and BP neural network model are combined, and then, the grey-neural network predicting model is proposed.Finally, in chapter six, a conclusion to the main research work in this paper was made, as well as some prospect to the further research.