Optimization of Cross-border E-commerce Supply Chain based on Fuzzy Control Algorithm in Digital Marketing

Based on fuzzy control algorithm, this paper proposes a new research framework for the optimization of cross-border e-commerce supply chain. Firstly, the challenges of cross-border e-commerce supply chain are analyzed, including complex international logistics, uncertain market demand and diversified regulations and policies. Then, the existing optimization methods are reviewed, and they are found to have some limitations. In order to overcome these problems, fuzzy control algorithm is introduced, and its theoretical basis and application are discussed in detail. Based on fuzzy control algorithm, a cross-border e-commerce supply chain optimization model is designed and simulated. The model covers key strategies such as dynamic inventory management, dynamic distribution and dynamic pricing, and demonstrates the potential of fuzzy control algorithm in supply chain optimization through the application of mathematical modeling and simulation data. The empirical results show that the strategy based on fuzzy control algorithm can significantly improve the operational efficiency of supply chain and reduce the total cost. However, it is also found that there are some problems in the empirical research, including the difficulty of data collection and the complexity of the model. In spite of this, fuzzy control algorithm still shows its potential in cross-border e-commerce supply chain optimization, and has feasibility and applicability. The research results provide an important reference for further exploration of fuzzy control algorithm in supply chain management. In this paper, the optimization of cross-border e-commerce supply chain is deeply studied and a new idea based on fuzzy control algorithm is proposed. The research results are of great significance for improving the efficiency and competitiveness of cross-border e-commerce supply chain, and provide useful enlightenment for academic research and practice in related fields. © 2024 CAD Solutions, LLC.