持有成本可縮減之隨機性存貨模型

Stochastic Inventory Models with Holding Cost Reduction

陳志忠(Chih-Chung Chen)

指導教授 ： 張宏吉 博士

國立臺中科技大學/商管學群/事業經營研究所/碩士(2007年)

摘要

在存貨管理領域中許多的研究都是以經濟訂購量(EOQ)模式為基礎，考慮現實環境的改變而修改部分假設，使建構的模型更能符合實際的應用。長久以來，單位持有成本經常被視為一固定的常數；直至最近，學者Billington (2003)才提出單位持有成本可透過增加投資支出而加以縮減的概念，而該研究仍以需求為已知的傳統EOQ模型為基礎。在現實的環境中，未來的需求充滿著不確定性，本論文的主要目的即是拓展Billington的研究至需求不確定的環境。
本研究是以一般常見的隨機性存貨模型為基礎 (即連續盤查及週期盤查存貨模型)，但放寬單位持有成本為常數的假設，進而建構單位持有成本可投資縮減的隨機性存貨模型。文中針對產品流動速度的快慢，分別考慮前置時間內之需求量(連續盤查)及保護期間內之需求量(週期盤查)為常態分配及Laplace分配兩種情形。在總成本最小化的目標下，透過計量方法分析模型之特性，並建立求解演算法，探討企業的最適投資及存貨策略。

關鍵字

存貨 ； 持有成本 ； 連續盤查 ； 週期盤查

並列摘要

In most of the early literature dealing with inventory problems, holding cost is viewed as a prescribed constant and is not subject to control. In practices, holding cost could be reduced by extra expenditure; in other words, it is controllable. Recently, Billington (2003) presented this idea and modified the classic EOQ model to include a reduction in the per-unit holding cost. One of the basic assumptions of EOQ model is that the demand is deterministic, while it is often with uncertainty. The aim of this research is to extend Billington’s work to the uncertain environments.
In this thesis, we propose two stochastic inventory models with holding cost reduction, based on the well-known continuous review and periodic review inventory systems. The demand during lead time (continuous review) is formulated by the Normal and Laplace distributions, concerning the fast- and slow-moving items, so does the demand during protection interval (periodic review). The objective is to minimizing the expected total annual cost by simultaneously optimizing the order quantity/review period, reorder point/target level and per-unit holding cost. For each model, a solution procedure is developed to find the optimal solution. Numerical examples along with sensitivity analysis are provided to illustrate the results of proposed models.

並列關鍵字

inventory ； holding cost ； continuous review ； periodic review

參考文獻

Ben-Daya, M. & Raouf, A. (1994). Inventory Models with Involving Lead Time as Decision Variable. Journal of the Operational Research Society, 45, 579-582.

Brown, R. G.. (1963). Smoothing, Forecasting and Prediction of Discrete Time Series. Englewood Cliffs: Prentice Hall.

Das, C. (1976). Explicit Formulas for the Order Size and Reorder Points in Certain Inventory Problems. Naval Research Logktics Quarterly, 23, 25-30.

Hariga, M. & Ben-Daya, M. (1999). Some Stochastic Inventory Models with Deterministic Variable Lead Time. European Journal of Operational Research, 113, 42-51.

Hariga, M. (2000). Setup Cost Reduction in (Q,r) Policy with Lot Size, Setup Time and Lead-Time Interactions. Journal of the Operational Research Society, 51, 1340-1345.