An adaptive joint replenishment policy for items with non-stationary demands

Abstract

This paper concerns the joint replenishment problem for a single buyer who sells multiple types of items to end customers. The buyer periodically replenishes the item inventory to order-up-to levels to cover the end customers' demands, which may be non-stationary. A joint replenishment policy characterized by a variable order-up-to level is proposed for buyers who wish to minimize the expected cost of operating the inventory system. According to the proposed policy, each period starts with calculation of the expected cost of two options, ordering and not ordering each item, based on a current inventory position and forecasted demand for the upcoming period. The proposed policy then uses an integer-programming model to generate a cost-minimizing decision for the joint replenishment. A computer experiment was performed to test the efficiency of the proposed policy. When compared with the most efficient policy currently available, our policy yielded considerable cost savings, especially for non-stationary demands.