Research on the optimization of the supplier intelligent management system for cross-border e-commerce platforms based on machine learning

At present, with the continuous development of the intelligent system, it is used in many industries. In e-commerce industry, the intelligent system has also been used, especially in supplier management. Based on the machine learning theory, this paper studies the optimization of the supplier management intelligent system of cross-border e-commerce platforms. Based on the wisdom algorithm and machine learning perspective, the optimization of cross-border e-commerce platform supplier credit system is studied in this paper. Firstly, the calculation of the traditional supplier credit evaluation is optimized by introducing the decision matrix algorithm of the difference matrix and the cloud model evaluation method. Then a multi-objective joint decision model of supplier selection and order allocation is established, and the multi-objective evolutionary algorithm combined with actual examples is applied to verify the effectiveness and feasibility of the algorithm and model. Finally, the decision makers’ preferences are integrated into the intelligent decision-making, and the cloud model evaluation method is adopted. The rough set and gray relational analysis mathematical tools are used to construct the procurement supply evaluation system. The research results show that the comparison of the three general indicators of the procurement supply chain can be obtained through the cloud model evaluation calculation, which indirectly reflects the preference decision weights of the three objective functions of the cross-border e-commerce supplier selection and order allocation multi-objective optimization model. This indicates that the procurement supply evaluation system constructed in this paper has achieved the purpose of scientific evaluation and selection of suppliers, and has played a theoretical reference role for supplier management of cross-border e-commerce platform.