Supply Chain

Supply chain management aims to optimize the flow of goods, information, and finances across interconnected entities, focusing on efficiency, resilience, and risk mitigation. Current research emphasizes the application of advanced machine learning techniques, including graph neural networks (GNNs), reinforcement learning (RL), and large language models (LLMs), to improve forecasting, risk assessment, and decision-making within complex supply chain networks. These models are being applied to various challenges, such as inventory management, fraud detection, and vulnerability identification, with a growing focus on incorporating causal inference and enhancing supply chain visibility. The resulting advancements have significant implications for improving operational efficiency, enhancing supply chain security, and fostering greater transparency and accountability across various industries.