Inventory policies under advance capacity information

Abstract

One of the most important challenges the inventory managers face is the uncertainty on both sides of the demand and supply. Exchange of information on both demand and capacity processes can decrease the uncertainty and it can be bene cial to all parties involved. But the quanti cation of the bene ts of information sharing is not easy. In this thesis our purpose is to see how managers utilize and integrate available advance information on capacity into the replenishment decisions, and identify the types of operating environments under which Advance Capacity Information (ACI) is most valuable. We consider a production/inventory system that faces stochastic demand, with a supplier whose capacity is limited and uncertain. But the supplier has agreed on sharing the capacity information for a certain number of future periods. We consider three di erent problems under these conditions. We rst model the rationing problem of a production/inventory system that serves customers from two di erent classes, which are distinguished by the penalty costs charged for unsatis ed demand. Then we study the ordering policies under average cost criterion. We propose heuristic approaches to calculate ACI-dependent order-up-to levels. The third problem we consider is of a rm that uses outsourcing whenever the in-house capacity is not adequate. We propose an ACIdependent order-up-to level policy, where ACI is de ned in terms of the distribution of the in-house capacity. Through numerical studies we derive managerial insights with respect to the bene ts of using ACI and the policies we propose.