The Can-Order Policy for One-Warehouse N-Retailer Inventory System: A Heuristic Approach

Abstract

We study an application of the can-order policy in one-warehouse n-retailer inventory system, and propose a heuristic approach for setting the appropriate inventory policy. On the can-order policy, an order is triggered when a retailer's inventory position reaches its must-order level. Then other retailers are examined whether their inventory reaches their can-order level, and if so they are filled by this order as well. Warehouse fulfills all involved retailers' inventory to their order-up-to levels. The can-order policy is not only able to save the total system-wide cost from joint replenishment, but it is also simple to use. Computer simulation is utilized to preliminarily study and to determine the best-known solution. We propose a heuristic approach utilizing decomposition technique, iterative procedure, and golden section search to obtain the satisfying total system-wide cost. This can save our computational time to find the appropriate inventory policy setting. We found that the proposed heuristic approach performs very well with the average cost gap less than 2% comparing to the best-known solution. It also provides satisfactory computational time from the reduced search space. Thus, the can-order policy can be very useful for such system.