Improved Demand Parameter Estimators in Inventory Problems

In stochastic inventory problems with unknown demand parameters, unknown parameters are typically replaced with their estimates before solving the inventory policy optimization problem. The hope is that the policy determined this way is satisfactory. This paper presents an analytical method that can be used to enhance unbiased estimators that are commony used. The method takes into account the impact of estimation errors on the inventory cost function. The method is developed grenerally for a class of inventory problems including problems with cost minimization objectives and problems with service achievement objectives. The method is applicable to problems where the demand has a probability distribution which belongs to the scale-location family. Examples with Normal and Gamma demand cases are presented.

By: Kaan Katircioglu; Derek Atkins

Published in: RC23805 in 2005


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