The Bayesian Approach to the Economics of One-Time Inventory Policy under Uncertainty

Abstract

This paper deals with the one time buy inventory problem of such products for which there is limited information available for demand prediction. The unknown mean demand is treated as random variable whose prior density is defined by a Beta density function. The Baye's rule is then used to redefine the economics of the inventory model under uncertainty about the mean demand. Assuming that no cost is incurred on collection of data, the expected cost of ignorance becomes the limiting value of the expected savings which accure due to the increase in knowledge about the true mean demand.