The integration of association rule mining and artificial immune network for supplier selection and order quantity allocation

This study firstly uses one of the association rule mining techniques, a TD-FP-growth algorithm, to select the important suppliers from the existing suppliers and determine the importance of each supplier. A hybrid artificial immune network (Opt-aiNet) and particle swarm optimization (PSO) (aiNet-PSO) is then proposed to allocate the order quantity for the key suppliers at minimum cost. In order to verify the proposed method, a case company’s daily purchasing ledger is used, with emphasis on the consumer electronic product manufacturers. The computational results indicate that the TD-FP-growth algorithm can select the key suppliers using the historical data. The proposed hybrid method also provides a cheaper solution than a genetic algorithm, particle swam optimization, or an artificial immune system.