Inventory Management

Inventory management aims to optimize the balance between supply and demand to minimize costs and avoid stockouts, a crucial aspect of efficient supply chain operations. Current research emphasizes the application of advanced machine learning techniques, such as reinforcement learning (including deep Q-networks and actor-critic methods) and large language models, often within multi-agent systems, to handle complex, dynamic, and uncertain demand scenarios. These models are being enhanced with features like interpretability and privacy-preserving mechanisms to improve decision-making and address real-world constraints. The resulting improvements in forecasting accuracy, inventory optimization, and supply chain resilience have significant implications for businesses across various sectors.