Optimal reorder decision utilizing centralized stock information in a two-echelon distribution system

The objective of this paper is to develop an optimal reorder policy for a two-echelon distribution system with one central warehouse and multiple retailers. We assume the warehouse has centralized stock information and each facility uses continuous-review batch ordering policy. Since echelon stock policies may show poor performance for distribution systems, we propose a new type of policy that utilizes the centralized stock information more effectively. We define the order risk policy, which decides reorder time based on the order risk which represents the relative cost increase due to immediate order compared to delayed order. We formulate the order risk and prove the optimality of the order risk policy under the system assumption that the warehouse guarantees delivery within the fixed lead time. The order risk is derived from the marginal analysis. Since exact calculation of the order risk is complex, an approximation method is provided. Computational experiment that compares our policy with existing policies shows that a significant cost savings is obtained. The concept of the order risk can be extended to the other models.