Chinese residents’ cold chain logistics demand forecasting based on GM (1,1) model

Cold chain logistics is a complex system, involving the whole process of temperature control of the entire chain from the packaging, transporting, storage and consumption of the products. The meeting of the market demand must be based on the forecasting. The main goal of this study is to forecast product demand values for cold chain logistics from 2010 to 2015 in China using GM (1,1). The residents’ consumption data of refrigerated and frozen food ranging from meat to milk were obtained from the China statistical yearbook of 2005 to 2009. A gray forecast equation of cold chain logistics demand is established and estimated by DPS 7.05 software so as to confirm its scientific and accurate forecasting system. The results show all the prediction accuracy of GM (1,1) model of the refrigerated and frozen food demand of historical data reached level 1 except average residual error, which reached level 2. So, we can see that the previous established GM (1,1) models have achieved good prediction effect. Meanwhile, by 2015, the amounts of products transported under refrigeration condition will be more than 55,649 tons, with a 4.3 proportion growth per year in the period of 2010 to 2015. Key words: Cold chain logistics, demand forecasting, grey model, China.