Using Scheduled Ordering to Improve the Performance of Distribution Supply Chains

We study a supply chain with one supplier and many retailers that face exogenous endcustomer demands. The supplier and the retailers all try to minimize their own inventory-related costs. In contrast to the retailers’ newsvendor type ordering behavior (under which retailers may place orders freely in every period), we propose two scheduled ordering policies: Scheduled Balanced Ordering Policy (SBOP) and Scheduled Synchronized Ordering Policy (SSOP). Under both SBOP and SSOP, retailers are allowed to order freely only in one period of an ordering cycle, and receive fixed shipments in other periods. However, SBOP is different from SSOP in that, retailers take turns to order freely under SBOP, while under SSOP, all retailers order freely in the same period. With the average supply chain cost per period as the performance measure, we identify mathematical conditions under which the scheduled ordering policies outperform the newsvendor type ordering. Through a large scale numerical study, we find that scheduled ordering policies are most effective when (i) the supplier’s holding and expediting costs are high; (ii) the end-customer demand correlation is high; and (iii) the supplier’s capacity is high. Further, we find that the performance of the scheduled ordering policies is fairly close to one another for different magnitudes of the end-customer demand variance. In addition, we observe that the behavior of SSOP often complements that of SBOP. While SBOP is better than SSOP when the supplier’s capacity is low and when the end-customer demand correlation level is high, SSOP is better when the opposite conditions hold.