A Bayesian Approach to Estimating Decision Parameters in a Replacement Inventory System

Abstract

This paper deals with the estimation of decision parameters in a special class of inventory systems in which the rate of stock depletion depends on the internal operations of the parent organization instead of market demands. Stocking decisions for this type of inventory systems are unique in that demands for the stocked items are internal demands, sporadic in some instances, infrequent in others, and almost never the direct results of conscious economic decisions. To cope with the peculiar situation, Bayesian point and interval estimation procedures are used. The estimated probability measures provide a basis on which stocking decisions pertinent to this type of inventory systems can be made or evaluated. Specific statistical postulates are made, and a numerical example is given for illustration. The possibility of applying the estimated results to one of the existing inventory models is briefly discussed at the end.