Beer game order policy optimization under changing customer demand

The present work analyses the optimal Beer Game order policy when customers demand increases. The optimal policy is found by means of a Genetic Algorithms (GAs) technique. GAs are specially suited for this problem because of the high dimension of the search space, and because the objective function, i.e. the global score of the chain, has many local minima. Our results show that the best performance of the chain is obtained when the sectors have different order policies. The advantage increases with the increasing change in the customer demand.