Distribution Requirement Planning and Inventory Policies for a Distribution Supply Chain with a Minimum Order Quantity

Motivated by a real-world application, the proposed project will consider a supply chain with one distribution center (DC) and multiple retailers which face exogenous stochastic demands. The retailers replenish their stock from the DC, which in turn replenishes from an external source. The supply chain is operated under installation-stock based (or semi-decentralized) control. Linear purchasing costs will be considered, but the DC must order either none or at least as much as a minimum order quantity (MOQ). The objective is to minimize the costs for ordering, for capital tied up in the supply chain, and for not providing an adequate customer service.In the actual application, the distribution requirement planning framework (DRP) was suggested for the system inventory control. DRP is a time-phased replenishment approach in which orders are generated periodically, based on demand forecasts over the leadtime, inventory and outstanding order status. The concepts and logic used are similar to those of material requirements planning (MRP), yet their connections with multi-echelon inventory models are different. Safety stocks are used to cope with uncertainties. The safety stock at each location is determined according to the forecasting errors over the (average) leadtime and certain service level requirement. Clearly, this logic is based on the simple-location setting, the solution of which is hence far from optimal. Only a few studies have provided results that can be used to determine the safety stocks in the DRP framework. However, they do not consider the MOQ. The primary purpose of the proposed study is to develop implementable procedures that on one hand, incorporate the MOQ, and on the other, can help improve the performance of DRP. The contribution lies in the effort towards bridging the gap between multi-echelon inventory theory and the DRP practice.