Exponential smoothing forecasts: taming the bullwhip effect when demand is seasonal

In this paper, we study the influence of seasonal demands and forecasts on performance an Automatic Pipeline, Variable Inventory, Order-Based, Production Control System (APVIOBPCS) using linear control theory. particular, consider a system that uses forecast based no-trend, additive-seasonality exponential-smoothing model, compare its to equivalent simple exponential smoothing. We find with forecasting significantly outperforms smoothing under certain demand assumptions. With optimal parameter settings, error model can be up 40% lower. However, also superiority does not necessarily translate measured through bullwhip metrics. addition, is very sensitive frequency parameters, while robust. This implies real life benefits implementing are obvious depend particular situation; large number settings (e.g. low seasonality, high-smoothing), good certainly justifies popularity in industry research worlds alike.