An integrated method to discovering key suppliers in supplier chain management

作者：Xu Xu; Lin Jie^*

来源：Journal of Computational Information Systems, 2009, 5(3): 1445-1452.

• Association rule mining
• Chain management
• Complex decision
• Data entities
• Data mining technology
• Data sets
• Essential characteristic
• Integrated method
• Numerical example
• Quantitative factors
• Supplier Selection
• Supplier selection process

Essential characteristics and criteria of suppliers are identified that must be considered in the supplier selection process. The analytic hierarchy process (AHP) is shown to be the appropriate methodology for evaluating and ranking potential suppliers. Supplier selection is not only a significant work in supply chain management but also a complex decision making problem which includes both qualitative and quantitative factors. Association rule mining is widely used data mining technology that searches through data set for rules revealing the nature and frequency of relationships between data entities. Mostly, there will be thousands of potential suppliers and a complicated process of determining a satisfactory subset based on many essential factors. In this article, the key supplier selection can be viewed as the problem of ranking the candidate supplier and mining a large of database of shipment. This search can be integrated AHP with association rule mining. The paper has employed a numerical example for the integrated method for suitable supplier set. The results show that the method is effective and feasible.

• 出版日期2009
• 单位同济大学