Column Generation

Column generation is an optimization technique used to solve large-scale linear programs by iteratively adding variables (columns) to a smaller, manageable problem. Current research focuses on accelerating this iterative process, often by integrating machine learning models such as neural networks, graph neural networks, and reinforcement learning agents to improve column selection strategies and predict optimal solutions. This leads to significant improvements in solving complex problems across various domains, including vehicle routing, scheduling, and classification, ultimately enhancing the efficiency and scalability of optimization algorithms for real-world applications.