An Optimize Design And Study Of Virtual Supply Chain System Of Auto Parts Industry Based On Interactive Decision

The 21st century is the "cooperative competition" or "supply chain and the supply chain competition" era. China's entry into the WTO that China's auto industry faces from the international markets to be more severe challenges. The automobile industry only way to survive is to implement the theme that is built for the Road network of supply chain management information. In a relatively short time, the Ability of auto industry supply chain management should improve what is a key problem for China's face international competition.On the basis of the author's work in the virtual supply chain system for Auto Parts Industry, the author mainly has done below the multi-analysis researches from following several aspects to this system:1. First, the author discussed the goal and the significance of this article, elaborated the importance of the supply chain and supply chain management; then, the author introduced the Virtual Supply Chain study the situation on domestic and foreign, and analyzed the problems and development In this field.2. The author introduced automobile industry supply chain system development stage, the basic principle and the development trend, and discussed the multi-objective decision-making and BP neural network development process, and a theory of knowledge. Made Auto Parts Industry Virtual Supply Chain platform, and proved its feasibility.3. The author analyzed features for Automobile Parts of the industry, particularly small and medium-sized enterprises of Auto Parts, reference multiple supply chain formation evaluation indexes and made for Auto Parts Industry Virtual Supply Chain formation evaluation indicators.4. The author designed a Virtual Supply Chain system for Auto Parts Industry, Analyzed the key issue of developing system, the overall system design, the part of the flow chart and functional modules, and database design. Focus on the process of formation of Virtual Supply Chain, used interactive decision-making algorithm to optimize its design and uses BP neural network has been optimized design improvements.5. The author completed this system contact surface design, and has carried on the actual movement, has achieved effective conclusion.