在全球化經濟及供應鏈管理的趨勢下，企業需透過與外部資源的整合以產生競爭力，供應商的選擇對於企業來說已經成為一個控制產品成功與否的關鍵因素，如何幫助企業選擇正確的供應商是一個急迫且待解決的問題。另一方面，企業與供應商已從傳統的敵對關係逐漸轉向為相互依存的合作關係，企業的管理範圍已從內部運作擴及外部供應商，因此，如何協助與管理供應商，讓他們成為供應鏈的助力，也是企業必須面臨的問題。
本研究以某企業供應商為研究對象，以類神經網路(Neural Network)及關聯規則(Association Rule)建立供應商評選模式。第一階段應用類神經網路(Neural Network)中的倒傳遞網路(Back Propagation Network, BPN)建立供應商評等之分類，以區分供應商之績效類別，同時進行模式訓練及驗證，以確保模式之穩定性；第二階段利用類神經網路分類後之供應商資料，以關聯規則(Association Rule)找出不同類型供應商之特徵及規則；最後利用類神經網路分類及關聯規則資料建立供應商評選模式，提供企業選擇供應商決策之參考，提升供應鏈管理的績效。

Under globalization environment, enterprises need to integrate external resources to increase competitiveness. How to help companies in selecting proper suppliers has become an important issue. In this study, we use Neural Network and Association Rules to establish a supplier selection model. The first phase adopts Back Propagation Network(BPN) to establish supplier rating classification. It aims to distinguish between providers of performance categories, while a model training and certification to ensure that Model of stability. The second phase trains association rule to identify different types of characteristics of each classification. A selection model has been proposed to combine the rule information and neural network classification to establish supplier selection model. The suggested supplier list provide a reference for decision-making in supplier selection which should be able to enhance the performance of supply chain management.

楊政麟. (1997). 運用類神經網路於股價指數套利之研究. 國立台灣科技大學管理技術研究所.
夏郭賢, 吳漢雄. (1998). 灰關聯分析之線性數據前處理探討. 灰色系統學刊, 1(1), 47-53.
葉怡成. (2001). 類神經網路模式應用與實作. 台北: 儒林圖書公司.
Agrawal, R., Imielinski, T., & Swami, A. (1993). Mining association rules between sets of items in large databases Paper presented at the Proceedings of the 1993 ACM SIGMOD International Conference on Management of Data. Washington, DC.
Berry, M. J., & Linoff, G. (1997). Data Mining Technique for Marketing, Sale, and Customer Support. New York: John Wiley & Sons, Inc.
Bhutta, K. S., & Hug, F. (2002). Supplier selection problem: a comparison of the total cost of ownership and analytic hierarchy process approaches, Supply Chain Management: An International Journal, 7(3), 126-135.
Boer, L. d., & Wegen, L. L. M. v. d. (2003). Practice and promise of formal supplier selection: a study of four empirical cases. Journal of Purchasing and Supply Management, 9(3), 109-118.
Braglia, M., & Petroni, A. (2000). A quality assurance-oriented methodology for handling trade-offs in supplier selection. International Journal of Physical Distribution & Logistics, 30(2), 96-112.
Caddick, J. R., & Dale, B. G. (1987). The determination of purchasing objectives and strategies some key influences. International Journal of Physical Distribution and Material Management, 17(3), 5-16.
Chen, M. S., Han, J., & Yu, P. S. (1996). Data mining: an overview from a database perspective. IEEE Transactions on Knowledge and Data Engineering, 8(6), 866-883.
Davies, P. C. (1994). Design issues in neural network development. NEUROVEST Journal, 5(1), 21-25.
Dickson, G. W. (1966). An analysis of vender selection systems and decisions. Journal of Purchas, 2(1), 5-17.
Ellram, L. M. (1990). The supplier selection decision in strategic partnership. International Journal of Purchasing and Materials Management, 26(4), 8-14.
Fan, A., & Palaniswami, M. (2000). Selecting bankruptcy predictors using a support vector machineapproach. Paper presented at the Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on.
Fayyad, U. M. (1996). Data mining and knowledge discovery: making sense out of data. IEEE Expert, 11(5), 20-25.
Fong, J., Hughes, J. G., & Zhu, J. (2000). Online web mining transactions association rules using frame metadata model. Paper presented at the First International Conference on Web Information Systems Engineering (WISE'00).
Frawley, W. J., Piatetsky-Shapiro, G., & Matheus, C. J. (1991). Knowledge discovery in databases: an overview. AI Magazine, 13(3), 57-70.
Freeman, J. A., & Skapura, D. M. (1991). Neural networks: algorithms, applications, and programming techniques. Redwood City: Addison Wesley Longman Publishing Co., Inc.
Han, J., & Kamber, M. (2006). Data Mining: Concepts and Techniques. San Francisco Elsevier.
Haykin, S. (1999). Heuristics for making the back-propagation algorithm perform better (2nd Edition ed.). New Jersey: Printice Hall.
Hornik, K., Stinchcombe, M., & White, H. (1989). Multilayer feedforward networks are universal approximators. Neural Networks 2(5), 359-366.
Khalfan, A., & Gough, T. G. (2001). Vender selection criteria and post-implementation evaluation practices for IS/IT outsourcing: a case study of a developing country. Paper presented at the Seventh European Conference on IT Evaluation.
Lee, H. (2000). Supplier selection and evaluation through activity-based costing approach. Industrial Engineering / Pusan National University.
Lehmann, D., & O'Shaughnessy, J. (1974). Difference in attribute importance for different industrial products. Journal of Market, 38(2), 36-42.
Liao, S. H., & Chen, Y. J. (2004). Mining customer knowledge for electronic catalog marketing. Expert Systems with Applications, 27(4), 521-532.
Bevilacqua, M., Petroni, A. (2002). From traditional purchasing to supplier management: a fuzzy logic-based approach to supplier selection. International Journal of Logistics, 5(3), 235-255.
Olhager, J., and Selldin, E. (2004). Supply chain management survey of Swedish manufacturing firms. International Journal of Production Economics, 89(3), 353-361.
Patton, W. E. (1996). Use of human judgment models in industrial buyers' vendor selection decisions. Industrial Marketing Management 25(2), 135-149.
Saaty, T. L. (1980). The Analytic Hierarchy Process. New York: McGraw-Hill.
Tagaras, G., & Lee, H. L. (1996). Economic models for vendor evaluation with quality cost analysis. Management Science, 42(11), 1531-1543.
Vellido, A., Lisboa, P. J. G., & Vaughan, J. (1999). Neural networks in business: a survey of applications (1992-1998). Expert Systems with Applications, 17(1), 51-70.
Weber, C. A., & Current, J. R. (1993). A multiobjective approach to vendor selection. European Journal of Operational Research, 68(2), 173-184.
Weber, C. A., Current, J. R., & Benton, W. C. (1991). Vendor selection criteria and methods. European Journal of Operational Research, 50(1), 2-18.
Weber, C. A., Currentb, J. R., & Desaic, A. (1998). Non-cooperative negotiation strategies for vendor selection. European Journal of Operational Research, 108(1), 208-223.
Weber, C. A., and Desai, A. (1996). Determination of paths to vendor market efficiency using parallel coordinates representation: A negotiation tool for buyers. European Journal of Operational Research, 90(1), 142-155.
Zhang, G., Hub, M. Y., Patuwob, B. E., & Indro, D. C. (1999). Artificial neural networks in bankruptcy prediction: General framework and cross-validation analysis. European Journal of Operational Research 116(1), 17.