The Dynamic Lot Size Model with Stochastic Demands: A Decision Horizon Study
INFOR, Vol. 26, Issue 3, pp. 213-224, 1988
13 Pages Posted: 21 Jun 2009 Last revised: 19 Oct 2010
Abstract
In a multiperiod decision problem it is usually the decisions in the first or first few periods that are of immediate importance to the manager. Decision/Forecast horizon (DH/FH) research deals with the question of whether optimal decisions in the first or first few periods (known as DH) can be made without regards to the data from some future period (known as FH) onwards. In this paper the Dynamic Lot Size Model (DLSM) with stochastic demands is studied. The model has a setup cost and hence does not have a convex cost strvicture usually assumed in the earlier DH/FH research involving stochastic problems. It is shown that in the stochastic DLSM, unlike in the convex cost problems, there are examples without DH/FH. However, randomly generated problems seem universally to have decision horizons. Sufficient conditions for the existence of DH/FH are obtained in terms of salvage functions, in terms of states of the system, and in terms of decision strategies. A comparison of these approaches concludes the paper.
Keywords: Decision horizon, forecast horizon, stochastic demands, concave cost, dynamic lot size model, Wagner Whitin algorithm
JEL Classification: M11, C61
Suggested Citation: Suggested Citation
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