在實務上，供應商通常提供零售商一段信用交期，所以零售商不需要立即提供貨款。另外，無線射頻辨識(RFID)在製造過程中被廣泛的應用在識別、追蹤以及訊息追蹤。傳統的經濟生產批量(EPQ)模型中假設全部產品皆為完美品質，但通常是不真實的。部分缺貨在現今交易中也是常見的。本論文發展非完美經濟生產批量模型之下採用無線射頻辨識、信用交易以及不良品的重工。兩種不同的模型被考慮: (1) 無部分缺貨 (2) 部分缺貨是被充許的。第一個模型目標是決定最佳的生產批量與RFID投資參數使總變動成本最小化。第二個模型目標是決定最佳的生產批量、最大允許欠撥水準與RFID投資參數使總變動成本最小化。根據週期時間及信用交期，模型演化成四種不同的情況。本論文針對上述的二個問題提出演算法求解。每個模型中，我們討論對於生產決策及總變動成本在不同系統參數的影響。根據數值分析提出管理意涵。

　　In practice, suppliers usually provide retailers with a credit period so that they do not need to provide payment for goods immediately. Also, radio frequency identification (RFID) is widely used to identify, trace, and track information during manufacturing processes. The traditional economic production quantity model assumes all products are of perfect quality, which is often not true. Partial backlogging is also common in today’s business. This paper develops imperfect economic production quantity models under RFID adoption, trade credit and reworking of imperfect products. Two different models are considered: (1) no partial backlogging and (2) partial backlogging is allowed. The objective of the first model (no partial backlogging) is to determine the optimal production quantity and RFID parameters to minimize the total variable cost. The objective of the second model (partial backlogging is allowed) is to determine the optimal production quantity, maximum backlogging level allowed and RFID parameters to minimize the total variable cost. Based on the cycle time and credit period, the proposed models are evolved into four different cases. This paper provide algorithms to solve the two problems. For each model, we discuss the influences of different system parameters on production decision and total variable cost. Some management insights are provided based on the numerical study.

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