Analysis of a Forecasting-Production-Inventory System with Stationary Demand

L. Beril Toktay () and Lawrence M. Wein ()
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L. Beril Toktay: Technology Management, INSEAD, 77305 Fontainebleau
Lawrence M. Wein: Sloan School of Management, MIT, Cambridge, Massachusetts 02142

Management Science, 2001, vol. 47, issue 9, 1268-1281

Abstract: We consider a production stage that produces a single item in a make-to-stock manner. Demand for finished goods is stationary. In each time period, an updated vector of demand forecasts over the forecast horizon becomes available for use in production decisions. We model the sequence of forecast update vectors using the Martingale model of forecast evolution developed by Graves et al. (1986, 1998) and Heath and Jackson (1994). The production stage is modeled as a single-server, discrete-time, continuous-state queue. We focus on a modified base-stock policy incorporating forecast information and use an approximate analysis rooted in heavy traffic theory and random walk theory to obtain a closed-form expression for the (forecast-corrected) base-stock level that minimizes the expected steady-state inventory holding and backorder costs. This expression, which is shown to be accurate under certain conditions in a simulation study, sheds some light on the interrelationships among safety stock, stochastic correlated demand, inaccurate forecasts, and random and capacitated production in forecasting-production-inventory systems.

Keywords: Forecasting; Martingale Model of Forecast Evolution; Production/Inventory; Stochastic Models; Queues; Diffusion Models (search for similar items in EconPapers)
Date: 2001
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Citations: View citations in EconPapers (41)

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