This research introduces a hybrid approach that combines Large Language Models with traditional metaheuristic algorithms to solve complex optimization problems more effectively.

• Leverages LLMs as pattern recognition tools within metaheuristic frameworks
• Outperforms existing state-of-the-art approaches that combine machine learning with metaheuristics
• Tested successfully on social network-based combinatorial optimization problems
• Demonstrates a practical integration of AI language models into engineering optimization techniques

This innovation matters for engineering because it creates more powerful tools for solving complex optimization challenges in fields like logistics, network design, and resource allocation—problems that traditionally require significant computational resources.

Metaheuristics and Large Language Models Join Forces: Toward an Integrated Optimization Approach