Research On Suppliers Selection And Evaluation Based On BP Neural Network

The rapid development of information technology and economic globalization brings a series of new harsh economic competition pressure to the enterprise. To meet the market demand for the modern environment, enterprises must coordinate and integrate resources to improve the competitiveness of the entire supply chain. As the source of the entire supply chain, supplier is an important link of supply chain optimization, bringing the core competitiveness of enterprise into full play.In this background, this paper combines qualitative and quantitative research methods, for supplier selection and evaluation of in-depth study and research. First, it introduces the research background and significance of paper, summarizes the status quo of supplier selection and evaluation both at home and abroad. Second, based on supplier selection and evaluation theories, defines the related concepts such as supplier and artificial neural network. On the basis of referential review, followed the setting principles of comprehensive concise, objective and comparable, operability, scalability, the author establishes the choosing and evaluating index system, which includes eight first-grade indexes such as product quality, product price, delivery time, production capacity, new product development level, informatization level, financial status and after-sales service, and nineteen second-grade indexes such as ISO quality authentication, qualified products and repair return rate, price and delivery time, order fill rate, annual production capacity, flexible, flexible, number of time, the R&D funding of flexible varieties, new product sales ratio, professional ratio, the use of information systems and maintenance level, asset returns, flow rate, and customer complaint asset-liability ratio, customer satisfaction rate of response to complaints. Furthermore using BP neural network theory, considering the selection and evaluation index of supplier, constructs the supplier selection and evaluation model based on BP neural network. Takes input data as the primary data sample, carries on the training and simulating after the network, and calculates the forecast value and the actual value error for selecting qualified suppliers. Then the BP neural network model for supplier selection and evaluation has been carried out by MATLAB toolbox, divided into three modules: the data module, network module and output module. Finally through A's application example, this paper gives a detailed introduction to application process and steps of MATLAB implementation of the BP neural network based model of selecting the supplier. At the same time makes a verification analysis on the method of supplier selection an evaluation based on BP neural network which is a feasible and effective method. Hope that the research method and conclusions in this paper can provide reference for the selecting and evaluating of suppliers both in theory and practice.