Optimization Tool

Optimization tools are being significantly enhanced by integrating machine learning, particularly large language models (LLMs) and graph neural networks, to automate problem formulation and solution finding across diverse fields. Current research focuses on improving the efficiency and scalability of these hybrid approaches, often employing techniques like mixed-integer linear programming (MILP) and surrogate-assisted optimization to handle complex, computationally expensive problems. This work has the potential to democratize access to advanced optimization techniques, enabling broader application in areas like manufacturing, energy management, and healthcare, where optimal solutions are currently often unattainable due to expertise and computational limitations.