實務上就－賣場而言，其顧客到達之間隔時間與每位顧客所購買之商品數量，皆可視為－隨機變數，在此情況下如何進行存貨管控及採購策略以使利潤達到最大化，對企業而言將是非常重要的議題。然而，不同商品之保存期限與需求量皆不盡相同，故在考量各種不同參數之條件下，如何找出最適訂購量即為本研究之探討重點。本文由間隔時間的觀念切入，經由實際觀測與統計理論之推導，將間隔時間的推算與易腐性商品之訂購策略進行結合，找出兩者之間的關聯性後，再針對傳統報童模式之相關內容進行分析與推導，並對相關參數進行敏感度分析，以期能對實務之運用有所貢獻。最後列舉範例進行驗證與說明，並提出四點具體結論供後續研究之參考。

In the real world, the time interval of each customer into a store and the quantities of products bought by customers can be seen as a random variable. Under this circumstance, it is a very important issue for retailer to control the inventory and ordering strategies to make the best profit. However, the expired date and the demand of products are different. Therefore, the main purpose of this study is to find the optimal ordering quantity under the consideration for different parameters. This research is developed from the concept of time interval and random product’s demand. Through the data collection of practical observation and the characteristics of perishable goods, the researcher can inference the demand distribution of perishable goods by applying statistical theory. Thus, the mathematical models can be developed to find out the optimal ordering quantity to maximize the total expected profit and then sensitivity analysis is taken for system parameters. Finally, a numerical example is demonstrated and the researcher derived four specific conclusions for further studies and practical application.