Machine Learning Approaches for Optimizing ERP Supply Chain Management with Ant Colony Optimization and GBDT

The impact of an ERP system's implementation on a company's supply chain system is investigated in this study. Supply chain design is emerging as a key competency in supply chain management (SCM), which is expected to integrate the enterprise resource planning (ERP) system as a basic component. Although Enterprise Resource Planning (ERP) software offers a range of capabilities to facilitate supply chain integration, there are some features that hinder ERP from integrating with other business operations. Preprocessing, feature extraction, and training the model are the three steps that make up the proposed technique. Data cleansing, data integrations, data transformation, data reduction, and data scaling are the five primary activities of data pre-processing. Principal component analysis (PCA) is utilized in component extraction. We used MACO-GBDT to train the model. This cutting-edge method outperforms MACO and GBDT with an average accuracy of 93.28 percent.