Exploring Combinatorial Problem Solving With Large Language Models: A Case Study On The Travelling Salesman Problem Using GPT-3.5 Turbo

Abstract

Large Language Models (LLMs) are deep learning models designed to generate text based on textual input. Although researchers have been developing these models for more complex tasks such as code generation and general reasoning, few efforts have explored how LLMs can be applied to combinatorial problems. In this research, we investigate the potential of LLMs to solve the Travelling Salesman Proble