運輸容量限制受限之多階多產品存貨模式

Multi-Item and Multi-level Inventory Management with Transportation Capacity Constraint

潘恩康(Eko Pratomo)

指導教授 ： 黃惠民

中原大學/電機資訊學院/工業與系統工程研究所/碩士(2014年)

https://doi.org/10.6840/cycu201400255

摘要

傳統的經濟訂購量模式(EOQ)只有考慮持有成本與設置成本，運輸成本往往被忽略或是被包含在設置成本當中。且單一產品的運輸成本占年度總物流成本的一半以上，因此，所有存貨模式皆須考量運輸成本的影響。再者，在多階存貨系統中，物流中心與零售商間的存貨關係亦是影響存貨模式。而且整數比策略是用來協調與解決零售商與物流中心間存貨關係的有效方法之一，其目的是為了要最小化系統存貨成本以及在處理接單、檢驗與出貨流程更加地順暢。
本研究在運輸容量限制受限之多階多產品存貨模式。其運輸類型考量自有車輛、租賃車輛及零擔運輸。研究之目的為推導出最佳訂購數量，使其總成本最小化。因此本研究將運輸成本納入經濟訂購量模式(EOQ)之中，並提出一個有效的求解流程。後續經由數值分析與敏感度分析驗證本研究所提出之模型。

關鍵字

租用車輛 ； 運輸容量限制 ； 自有車輛 ； 多產品 ； 整數比策略 ； 多階存貨

並列摘要

The classical Economic Order Quantity (EOQ) captures only the trade-off between inventory carrying cost and setup; transportation cost is either neglected or included in set up cost. Over 50% of the total annual logistics cost of a product can be attributed to transportation, thus any consideration of purchase quantities should consider transportation costs. In multi-level inventory system, distributor and retailers need to synchronize their inventory. Integer Ratio Policies is one of the ways to coordinate the relationship between retailers and distributor. The aim is to minimize the system inventory cost as well as improving the scheduling, receiving, inspection and information processing tasks.
This research deals with multi-level multi-item inventory management considering transportation cost and capacity constraint. Three types of transportation are used; namely own vehicles, hired vehicles and Less than Truckload (LTL). The goal of this research is to determine the optimum order interval which results in minimum total cost. Transportation cost is also considered for deciding optimum solution. Solution algorithms to obtain the optimum values are proposed. Numerical examples and sensitivity analysis are performed to verify the effects of parameters change and the behavior of these models.

並列關鍵字

own vehicles ； multi-item ； multi-level ； transportation capacity ； Integer Ratio Policies ； hired vehicles

參考文獻

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