Genetic Algorithms in Seasonal Demand Forecasting

Demand forecasting is one of the most important phase of a firm’s decision making process. Management of material flow, which is based on just-in-time strategy, would not be possible to achieve without precise estimation of the demand. We can distinguish two general demand forecasting methods, namely quantitative and qualitative methods [2, 3, 6]. The advanced computer software that enables data computing and graphic presentation of data can support both of them. Artificial intelligence (AI) techniques (such as: genetic algorithms, fuzzy logic and neural networks) will be extensively applied in the next stage of forecasting methods development. Applying AI techniques should improve correctness of seasonal demand forecasting. A presentation of seasonal demand forecasting method and its applicability is the main objective of this article. Identification of demand function’s parameters is based on genetic algorithms (GA) approach.