Approximate Solutions of a Dynamic Forecast-Inventory Model

Authors:
Tetsuo Iida;Paul H. Zipkin
Affiliations:
School of Business Administration, Komazawa University, Tokyo 154-8525, Japan;The Fuqua School of Business, Duke University, Durham, North Carolina 27708-0120
Venue:
Manufacturing & Service Operations Management
Year:
2006

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Abstract

In this paper we consider a dynamic forecast-inventory model with forecast updates, based on the martingale model of forecast evolution. Two types of updates are considered, additive and multiplicative. The formulation of the model results in a dynamic program with multidimensional state space. We derive some characteristics of optimal policies and also develop a computational approach to obtain approximate solutions. The approach is based on simulation and function approximation.