Combined forecasting of regional logistics demand optimized by a Genetic Algorithm

Accurate prediction of regional logistics demand was the premise for scientific decision-making. On the basis of analyzing Trend Extrapolation, Grey System Method and Regression Method, two weight value determination methods that based on Method of Arithmetic Means and Validity Method were compared. Then, the idea of using a Genetic Algorithm to optimize weight values was put forward. The predicting outcomes of turnover volume of freight transport in region A turned out that the Genetic Algorithm can minimize the Sum of Squared Errors.