變動訂購期間定期盤存模式之研究

Abstract

許多商品向同一供應商購買時更是如此。但幾乎所有定期盤存模式皆假設訂購期間為固 定，而實務上訂購期間卻可能為變動。此現象主要肇因於供應鏈中之供應不確定，如供 應商拜訪下游零售商並補充存貨，但或因零售商散佈各處、或因供應商處於較有利位 置、或因供應商根本無既定拜訪時程，供應商並非固定間隔時間到達。在這些情況下， 零售商之補貨週期基本上是變動的。 本計畫使用動態規劃來處理上述供應鏈之情境。本計畫假設供應商之拜訪時程為獨 立且同質分配，初步研究結果顯示所導出之缺貨後補模式為文獻上標準之定期盤存問 題，另本計畫亦建議一個簡易的喪失銷貨模式。本計畫所發展之存貨政策易於為業界所 應用。 研究結果顯示忽略供應商拜訪時程之變動將導致零售商巨大的損失，特別是當需求 變異大或補貨時間長時更是如此。因此當供應商拜訪時程為變動時，採用本計畫所發展 的存貨模式就顯得非常重要。

Periodic review inventory models are widely used in practice, especially for inventory systems in which many different items are purchased from the same supplier. However, all periodic review models have assumed a fixed length of the review periods. In practice, it is possible that the review periods are of a variable length. Such periodic systems result mainly from supply uncertainties. For example, the supplier visits the downstream retailers and replenishes inventories for them, but does not always come in constant intervals. This may be because retailers are geographically dispersed in the supply chain, the supplier is in a relatively more powerful position, or the supplier simply does not have a reliable visit schedule. In such situations, the replenishment cycle length is random in nature. In this research, we use dynamic programming to model such institutional contexts. We assume that the supplier’s visit intervals are independently and identically distributed. With a suitable transformation, the backlogged periodic review model derived becomes a standard discrete-time model. We also suggest a simple heuristic for the lost-sales problem. The computation shows that ignoring the variability of the supplier’s visit intervals can incur extremely large losses, especially if shortage is costly, demand variability is low, and/or the replenishment lead-time is short.