Research On Evaluation Method Of Suppliers Of A Petrochemical Enterprise Based On BP Neural Network

With the development of the thought of supply chain and market competition intensifies, the enterprise production pattern has gradually transformed, already from the original pure competition between enterprises and suppliers relationship into a dual relationship between competition and cooperation. As one of the important part of the supply chain, the supplier management plays a very important role to enterprise’s development. The subject of supplier evaluation and selection has been taken seriously, on which many scholars and enterprises at home and abroad have do a lot of theoretical and empirical research.Company A is one of large-scale petrochemical enterprises in our country. Since its establishment, it has become an international energy company including oil and gas, refining, sales, financial services, natural gas and electricity, new energy and professional technical services business. Compared with other industry, the petrochemical industry has some special purchasing characteristics, such as much more categories, higher price, large batch, higher quality requirement. Therefore under the supply chain environment, combined with the actual situation of company A, a scientific and reasonable supplier selection evaluation system will play an important role to realize the selection of suppliers, reduce costs, improve production efficiency, and improve the core competitiveness for enterprises. At present although some scholars have researched on the petrochemical industry supplier evaluation standard, some evaluation indexes are old, and the systematic research is less for an enterprise, what’s worse, the evaluation methods is too subjective, which cannot provide adequate theoretical basis for evaluation of supplier selection for Chinese petrochemical enterprises.In view of the above problem, this article chooses company A as the research object and carries on a detailed research on the supplier evaluation question.First of all, the thesis studies the related literature at home and abroad, expounds the concept of supplier management as well as the importance of supplier evaluation, analyzes the research of supplier evaluation at home and abroad and summarizes the relevant theory of BP neural network.Secondly, in this paper, the characteristics of petrochemical industry suppliers and the present situation and problems of supplier evaluation has been analyzed, also the present situation of supplier management and the problems of the supplier evaluation of company A are studied. On this basis, with the method of literature study, questionnaire and factor analysis, this paper build the supplier evaluation indexes system of company A, and gives a detailed description of the various indicators.Finally, based on the comprehensive consideration of existing supplier evaluation methods, this paper selects the BP neural network to build supplier evaluation model.The model has the advantages of objectivity, dynamic, practical, and has good learning ability, which can avoid problems such as subjectivity. After collecting a large number of suppliers’related data, the neural network model is constructed by using the Matlab software to train and simulate, and verifies the validity and accuracy of the model.Research of this paper, closely combined with the actual demand of petrochemical enterprises in China, makes a detailed study on the supplier evaluation system of company A. The study also puts forward the evaluation indexes system and model of petrochemical enterprise in theory and practice, which has a good practice and reference significance to other petrochemical companies’supplier selection.