On the risk-based aggregate planning for seasonal products

In this paper a model is developed to analyze the effect of risk incurring at companies producing highly seasonal products. According to observations the closer to the season we are the better our knowledge on demand distribution. This fact is reflected by a learning effect in demand distribution applied in the model where the aim is to minimize the risk-connected costs originating from the unpredictable behavior of demand. The paper confirms that unpredictability is only one of the decisive factors in sequencing products, and other elements play an important role too. The paper presents forward and backward procedures for determining the production quantities and sequencing of the products in an aggregate planning horizon.