為了取得成功，企業必須平衡並正確地獲得三項重要的業務資源：產能、存貨與前置時間。為了增加市場競爭優勢，企業必須提高客戶滿意度和降低製造成本。在企業上時間和成本是最主要的競爭因子。因此，決策者必須規劃適當生產計劃和安全存貨量，才能降低訂購成本、存貨成本、缺貨成本及趕工成本。然而，由於現今市場環境的快速變遷下，存貨管理對於企業的營運績效更顯現出其重要性。所以如何有效的控制存貨水準已經變成企業管理者一個所必須要面對的議題。
本研究是連續盤查的存貨模式，共同確定了訂購數量、欠撥折扣、製程品質、前置時間和批次交貨等的最佳解。它們作為此允許缺貨發生，並在缺貨期間合併考慮欠撥與缺貨損失的整合存貨模型之決策變數。由於不同的顧客會有不同的前置時間需求，不可能僅以常態需求分配來表示前置時間的需求量。因此，本篇論文中提出二個存貨模型。一為前置時間內需求量的機率分配服從常態的情形，另一個則是當需求量的機率分配服從一般分配的情形。
研究中首先假定前置時間內需求量的機率分配服從常態的情形，並建立求問題最佳解的演算法；另一為前置時間內需求量的機率分配型式為未知，而僅已知其平均數與標準差的情形，並運用分配不拘大中取小準則來求得前置時間、欠撥折扣與安全係數等的最佳解。最後對於所提出的兩個模型，均將以數值範例進行說明。

In order to succeed, there are three critical operational resources that businesses need to balance and get "right": capacity, inventory and lead time. To increase the market competition advantages, enterprises must improve customer satisfaction and reduce the manufacturing cost. Therefore, we must plan a suitable schedule of production and amount of safety stock. It could reduce the cost in ordering cost, holding cost, stock-out cost, and lead time crash cost. However, the inventory problem plays a more important role in production management. It becomes a very important issue that how to efficiently control the inventory level.
In this study, we develop an integrated inventory model which jointly determines the optimal order quantity, backorder discount, process quality, lead time, quality improvement, and the frequency of deliveries simultaneously. They are considered as the decision variables of the integrated inventory model that is a mixture of backorders and lost sales. Because the demands of different customers are not alike in the lead time, it cannot only use a single distribution such as a normal distribution to describe the demand of the lead time. Therefore, there are two inventory models proposed in the paper, one with normally distributed demand, and another with generally distributed demand.
In this thesis, first assume that the lead time demand follows a normal distribution, and attempt to find the optimal solutions. Then, the next step relax this assumption by only assuming that the first and second moments of the probability distribution of the lead time demand, and then solve this inventory model with the minimax distribution free approach. After that develop algorithmic procedures to find the order quantity, optimal lead time, backorder discount, and safety factor. At last there are numerical examples to demonstrate solution procedure.

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