Reliable Prediction Intervals and Bayesian Estimation for Demand Rates of Slow-Moving Inventory Page: 16
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Continuous Review: (s, S) Model and (s, Q) Model
Under a continuous review inventory system for a single item with
stochastic demand, either the order point, order-up-to or (s, S) model or the order
point, order quantity or (s, Q) model may be used (Schultz, 1989). In other words,
whenever the inventory level drops to s units, an order is released to either bring
inventory up to S units or acquire Q units to replenish the stock. While rare in
practice, a basic assumption of the (s, S) model is that the demand and relevant
cost parameters, do not vary over time. Cohen, Kleindorfer, Lee, and Pyke
(1992) present optimal policies in an (s, S) model for stocking spare parts and
part families in a multi-echelon distribution system.
Despite being difficult to apply, (s, Q) models are common in the existing
literature and often recommended for spare parts inventory and high value, low
volume items (Razi & Tarn, 2003). Silver (1991) introduces a simple graphical
tool that is appropriate for slow-moving items in an (s, Q) model and can be used
to reduce inventory control costs. Chang et al. (2001) develop an (s, Q) model for
slow-moving inventory under the assumption of Laplace demand.
Assumptions of (s, S) Model
Several algorithms have been proposed to determine the optimal (s, S)
policy under different scenarios (Wagner, O'Hagan, & Lundh, 1965; Johnson,
1968; Schneider, 1978; Ehrhardt, 1979; Freeland & Porteus, 1980). In general,
the following four standard assumptions are made.
1. Demand is stationary for some period of time.
2. Demand is discrete.16
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Lindsey, Matthew Douglas. Reliable Prediction Intervals and Bayesian Estimation for Demand Rates of Slow-Moving Inventory, dissertation, August 2007; Denton, Texas. (https://digital.library.unt.edu/ark:/67531/metadc3946/m1/30/: accessed April 25, 2024), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu; .