Combined forecasting of regional logistics demand optimized by genetic algorithm

Purpose – The purpose of this paper is to establish a combined forecasting model to predict regional logistics demand, which is an important procedure on decision making of regional logistics planning. Design/methodology/approach – There are several kinds of mathematical models often used in forecasting regional logistics demand. Trend extrapolation method extrapolates the future development trends bases on the hypothesis that the regional logistics will develop steadily. Grey system method predicts the change of logistics demand by the generation and development of original data sequence and excavation of inherent rules of the original data. Regression method obtains the change rules through the analysis between explained variable and explanatory variables. Each method has unique characteristics. In order to improve the accuracy of the prediction, combined methods are established. Genetic algorithm is used to determine the weights of different single models. Findings – The results show that the combined ...