Minimization of bullwhip effect in face of different inventory policy

Abstract

There are four major causes of bullwhip effect – demand forecast updating, order batching, price fluctuation, and rationing and Shortage Gaming (Lee, 1997), which can be measured using the concept of Bullwhip Effect Index (BE) (Dejonckheere, 2003; Sterman, 1989). This report will focus on the first two causes – demand forecast updating and order batching – and adding two inventory policies into the analysis.

The reason of adding two inventory policies – (s,Q) Policy and (R,S) Policy – is because each inventory policy has different parameters to trigger the ordering signal, which result in different ordering frequency and quantity. Comparisons between these inventory models are established before the analysis is carried out. Finally, discussion to obtain the minimum bullwhip effect from combination of the inventory policies and, so, it can be used to optimize supply chain performance.

This FYP measures the impact of different parameters in (s,Q) Policy and (R,S) Policy with different ordering policy combination in 1 Manufacturer and 2 Distribution Channels network to the bullwhip effect by measuring the BE value. The result shows that the optimum combination will always occur in (s,Q) Policy, when the ordering quantity (Q) is equals to the average demand (μ). The same result also held in 1 Manufacturer and 2 Distribution Channels network, where two (s,Q) Policies with Q equals to μ.