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Staggered ordering policies for two-echelon production/distribution systems

Rungson Samroengraja, 1999
Faculty Advisor: Fangruo Chen
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We consider a class of ordering policies for a two-echelon production/distribution system. We envision N identical retailers being served by a central warehouse or factory. The key feature of the ordering policies is that the retailers' order occasions are staggered. The retailers are divided into equal sized groups. Only one group may order from the upper echelon at a time, the time between successive orders by the same group is identical for all groups and the time between any two successive orders received by the upper echelon is identical. While this type of policy is widely used in industry, it has received little attention in the multi-echelon inventory literature.

We propose two types of staggered ordering policies. The first policy addresses the situation where there are only fixed order costs at the upper echelon. The second policy considers a situation where there are fixed order costs at the retailers only and a capacity limit at the upper echelon. We provide exact evaluation methods for both under certain conditions. We also consider the use of staggered ordering policies in the context of reducing the bullwhip effect by managing the order volatility seen by the upper echelon. The bullwhip effect is believed to be a major cause for supply chain inefficiencies. We test whether managing order volatility through the use of staggered ordering policies leads to lower overall supply chain costs. We show that reducing order volatility does not guarantee a reduction in overall supply chain costs. Finally, we study the benefits of centralized demand information when using a staggered ordering policy under different allocation policies. We are able to provide exact evaluation methods for two types of information policies under certain conditions. A numerical study confirms that under certain circumstances, the use of centralized demand information can lead to a substantial reduction in overall supply chain costs.

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