The Determination of Optimal Suppliers for the Chain Restaurant Industry by Integrating a Modified LVQ Algorithm and the Gray Multi-attribute Decision

Using an intelligent supplier selection support structure to determine optimal suppliers, as based on the future development strategies of a company, is very important to the members of the chain restaurant industry in the current consumer demand-oriented market. Hence, this study conducted research in the following four parts: 1) supplier specification design, 2) the clustering design of the modified LVQ (Learning Vector Quantization) algorithm, 3) the characterization design of RST (Rough Set Theory), and 4) gray multi-attribute decision for optimized decision making of chain restaurant industry supplier selections. The research findings suggest that, in cases of three different raw materials in different clusters under analysis, costs can be reduced by at least 8.7% (NT$175, 036), indicating that the proposed supplier selection method can be applied to the chain restaurant industry.