Supply Chain Optimization

Supply chain optimization aims to design and manage the flow of goods and services to minimize costs and maximize efficiency. Current research focuses on improving prediction accuracy for demand and supply using techniques like graph neural networks and quantum-inspired machine learning, as well as developing more robust and adaptable optimization algorithms such as those based on reinforcement learning and consensus planning to handle complex, real-world constraints and uncertainties. These advancements are crucial for enhancing operational efficiency, reducing waste, and improving responsiveness across various industries, from consumer goods to healthcare.