Simulation model to analyze bullwhip effect under classical and information sharing ordering policies

The lack of coordination among supply chain members and the local optimization of each member for his own benefits without considering the impact on other members cause inefficiencies in supply chains. Bullwhip effect is one of these inefficiencies. Bullwhip effect has been defined as the amplification of demand information as it moves upstream the supply chain. This distortion in demand information leads to excessive inventories, insufficient capacities and high transportation costs. Extensive research has been done in order to identify the main causes of bullwhip effect. Ordering policies have been reported as one of the important operational causes of bullwhip effect. This paper investigates the impact of various classical ordering policies on inventories behavior in a supply chain through a simulation study. In addition, a proposed ordering policy that relies on information sharing is proposed to mitigate the bullwhip effect and overcome the problems of classical ordering policies. In the proposed policy, the information of customer demand and inventory adjustment is shared among supply chain partners in a decentralized way. A simulation model is built for a four-echelon supply chain, with deterministic ordering and delivery lead times, in order to quantify the supply chain dynamic performances under the different ordering policies, especially on the inventories. The simulation results show that the performance of the inventories in the supply chain is always instable under the classical ordering policies. The ordering policies that update its parameters corresponding to demand changes such as Order Up To replenishment always result in high bullwhip effect, high average inventory level, and high variance of inventory level. The policy that sends fixed ordering quantity such as (R, Q) can eliminate the bullwhip effect but fails to recover supply chain performance in terms of inventory level. The proposed ordering policy based on information sharing succeeds to mitigate the bullwhip effect and achieve an acceptable performance in terms of both average and variance of inventory level. In general, the proposed information sharing ordering policy realized a better performance than the classical ordering policies. This opens the way for designing new ordering policies based on information sharing to handle the problems of classical ordering policies.