Employing genetic algorithms to minimise the bullwhip effect in a supply chain

There has been considerable research interest in the last number of years demonstrating the effectiveness of genetic algorithms (GAs) to reduce the bullwhip effect in supply chain management. One criticism of this research is that the supply chain models employed have been unrealistic and consider only a few stages within a supply chain. In this paper, the authors present an improved supply chain model, which is based on the beer game and includes additional cost factors including ordering cost, distribution cost, production cost. GAs are then employed to determine the optimal ordering policy for each member in the model. Through the experimental results, this paper demonstrates that GAs can reduce the bullwhip effect and determine the optimal ordering policy even in more complex supply chains.