由於全球化的競爭，現今企業多講著重於提高效率及最小化成本，要達到上述目標之一就是外包。因此，供應商選擇成為實現競爭優勢的最重要因素。首先本研究使用關聯法則中的TD-FP-growth演算法，從現有的供應商中刪減不重要的供應商，這可以提供出關鍵供應商。然後，本研究提出整合最佳化人工免疫網路(Optimization Artificial Immune Network; Opt-aiNET)與粒子群最佳化演算法(PSO)為供應商訂購量分配的方法，建構出成本最小化的關鍵供應商訂單組合。
為了驗證所提出的方法，使用消費性電子產品製造商A公司的實際進貨資料。TD- FP- growth演算法可以挑選出關鍵供应商。此外，本研究所提出的整合最佳化人工免疫網路與粒子群最佳化演算法，與遺傳演算法、粒子群最佳化演算法以及最佳化人工免疫網路演算法相較下，真的可以得到最低的成本。

Due to global competition, most of the enterprises focus both on accelerating the implementation efficiency and minimizing the operation costs. One of the ways to achieve the above goals is outsourcing. Thus, supplier selection has become the most critical factor for achieving competitive advantage. This study first intends to employ one of the association rule mining techniques, TD-FP-growth algorithm, to prune off unimportant suppliers from the existing suppliers. This can provide us the key suppliers. Then, an integrated optimization artificial immune network (Opt-aiNET) and particle swarm optimization (PSO) is proposed to allocate the orders for the key suppliers with minimum cost.
In order to verify the proposed methods, a case company’s daily purchasing ledger focusing on the consumer electronic product manufacturers is applied. TD-FP-growth algorithm is able to select the key suppliers. Besides, the proposed method, integrated Opt-aiNET and PSO really can provide lowest cost compared to those of genetic algorithm, PSO, and Opt-aiNET.

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