Supply chain resource integration method under 4PL mode based on associated data

Abstract

The relevance of power supply chain resources is a key factor affecting the hit rate of resource integration. Therefore, a 4PL mode based supply chain resource integration method based on associated data is proposed. Firstly, analyze the functions of the power supply chain under the 4PL mode, mainly including intelligent procurement, digital logistics, panoramic quality control, supply chain collaboration, and operational compliance. Secondly, according to the basic characteristics of the 4PL model, which is intensive, valued, standardized, and internationalized, the Apriori association rule algorithm is used for association data mining of power supply chain resources. Finally, based on the results of power supply chain association data mining, the improved ant colony segmentation algorithm is used to divide the power supply chain knowledge base into modules, and the mapping principle is used to complete the integration of supply chain resources. The experimental results show that the proposed integration method realizes effective knowledge base mapping in the process of resource integration, which can improve the utilization of power supply chain resources and reduce energy consumption, with the integration hit rate reaching 99.04%.

Keywords

• associated data
• 4pl mode
• power supply chain
• resource integration