Large Language Models for Operations Research: A Comprehensive Survey

TL;DR

This is a comprehensive survey paper that systematically organizes methods for utilizing Large Language Models (LLMs) to solve Operations Research (OR) problems.

Problem

Traditional OR methods heavily rely on expert knowledge and struggle to efficiently solve large-scale, multi-constraint problems. The advancement of LLMs has opened a new research paradigm to address these challenges, but a systematic overview has been lacking.

Approach

The paper begins by introducing the definition of OR problems and the fundamental principles of LLMs. It then analyzes the roles of LLMs in OR, categorizing them into model formulation, algorithm design, and solution verification. It also summarizes practical applications in representative scenarios and benchmark datasets in the field, outlining key challenges and future research directions.

Results & Contribution

It provides the first comprehensive survey of the LLM4OR field, helping researchers understand how to apply LLMs to OR problems. By making a collection of related literature publicly available via a GitHub repository, it establishes a foundation for subsequent research.