在一般研究腐敗性商品或流行性商品時，我們通常假設淘汰時間為固定常數。但是，在現實生活中不管是零件或商品都有屬於自己的淘汰時間，並且大多時候你並不知道它被淘汰的時間點為何。進而隨著時間的淘汰，也會有淘汰成本。因此，在我們的研究中，假設有一產品的淘汰時間為隨機且非均值。根據此產品的特性下，找出符合它的訂貨策略。 在本篇文章中，我們探討的重點為多期存貨模型結合失效率函數。而本篇文章的目標為利用我們所提供的近似求解方法，在近似最低成本下求解出每期的最佳存貨水準與最佳再訂購點。在數值分析章節中，我們使用模擬方法探討兩種情況對於真實成本的影響。第一種情況為原始多期存貨模型，則第二種情況為加入淘汰成本的新模型。最後，我們會觀察模型中的參數對於存貨水準和總成本的影響，也會藉由韋伯分配來看失效率和存貨水準的關係。 For general order policy, we can see a lot of literature that describes much environment. Nevertheless, only a few literature describes the sale of life with consideration of nonhomogeneous random obsolete time. We assume a kind of products, whose life is stochastic. The products are phased out, as their life of sale is over. We construct the special scenario of our research. We consider a kind of product with obsolete time, and the lead time equals to zero. In other words, we order the product which is replenished to the stock level immediately. In this research, we only consider a single product. In the inventory model of our research, we combine multiperiod newsvendor model and nonhomogeneous random obsolete time, and construct a recursive function of dynamic programming with backward. The function includes the conditional probability of life, the phased out cost, the shortage cost, the holding cost and purchase cost in next period. In order to ordering the products, we optimize the function every period. Because we don’t know the time of phase out, we don’t have the optimal solution of total problem. We will simulate the order policy which is setted by us to represent the result in our study on the last chapter of numerical analysis.
