Fresh Agricultural Products Cold Chain Location Selection in Context of Big Data

Abstract

In the domestic fresh market, agricultural products are one of the major consumer goods. The rational optimization of the fresh agricultural products cold chain distribution center location is of great significance in enhancing the efficiency of the entire cold chain logistics. Therefore, in the context of big data, this paper chooses the grey forecasting method with a higher prediction accuracy, applied GM(1,1) prediction model for fresh agricultural products demand forecast under the premise of comparing different forecast methods' accuracy; Basing on the demand forecast, this paper formulates fresh agricultural products distribution center location model with the minimum total cost objective. In this objective, the thesis considers the cost of cargo damage and the penalty cost of violating the time window in order to this order to improve customer satisfaction and loyalty, which is considered by a few researchers. Finally, a specific case study is designed for Q enterprise to solve the optimal the result and test the validity of the model algorithm.