Evaluating supply partner's capability for seasonal products using machine learning techniques

We develop a dynamic partner assessment system in order to assess change in a supply partner's capability over a period of time. The system embeds a multi-criteria decision model and machine learning methods, and is designed to evaluate a partner's supply capability that can change over time and to maximize revenue with different procurement conditions across time periods. We apply the system to the procurement and management of the agricultural industry. The results are compared with real-world auction markets.