Author(s)

Chuanrong Lu, Yun He

Corresponding Author

Yun He

Abstract

This article discusses the application of big data analysis in the field of cold chain logistics. At present, cold chain logistics is developing rapidly, but it faces the problems of inaccurate demand forecast and unreasonable path planning. This article aims to improve the accuracy of cold chain logistics demand forecasting and the efficiency of path optimization with the help of big data analysis. In this article, literature research is used to sort out the relevant theoretical achievements, and a theoretical framework for the application of big data analysis in cold chain logistics is constructed through theoretical derivation. It is found that big data analysis can help cold chain logistics in many ways. In demand forecasting, through extensive data sources and preprocessing, a suitable forecasting model is constructed and the results are optimized. In the aspect of path optimization, strategies are formulated and algorithms are implemented according to big data. However, the application process faces challenges such as data security, technology integration and talent shortage. This article puts forward targeted countermeasures to promote the effective application of big data analysis in cold chain logistics and improve the overall efficiency of the industry.

Keywords

Big data analysis; Cold chain logistics; Demand forecast; Path optimization; Application challenge