# Exploring the Improvement of Evolutionary Computation via Large Language Models

arXiv: https://arxiv.org/abs/2405.02876 · HTML: https://mlsanity.com/paper/2405.02876/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 7 references that are in the map.
- First posted on arXiv 5 May 2024.

## Builds on (most cited first, 3 of 3)

- [ReEvo: Large Language Models as Hyper-Heuristics with Reflective Evolution](https://mlsanity.com/paper/2402.01145/) (2024)
- [Large Language Models as Evolutionary Optimizers](https://mlsanity.com/paper/2310.19046/) (2023)
- [ChatGPT and Other Large Language Models as Evolutionary Engines for Online Interactive Collaborative Game Design](https://mlsanity.com/paper/2303.02155/) (2023)

## Built on by (most cited first, 4 of 4)

- [Large Language Models in Operations Research: Methods, Applications, and Challenges](https://mlsanity.com/paper/2509.18180/) (2025)
- [Towards Engineering Multi-Agent LLMs: A Protocol-Driven Approach](https://mlsanity.com/paper/2510.12120/) (2025)
- [Can Large Language Models Be Trusted as Evolutionary Optimizers for Network-Structured Combinatorial Problems?](https://mlsanity.com/paper/2501.15081/) (2025)
- [Automatic Adaptation Rule Optimization via Large Language Models](https://mlsanity.com/paper/2407.02203/) (2024)

## Abstract (arXiv)

Evolutionary computation (EC), as a powerful optimization algorithm, has been applied across various domains. However, as the complexity of problems increases, the limitations of EC have become more apparent. The advent of large language models (LLMs) has not only transformed natural language processing but also extended their capabilities to diverse fields. By harnessing LLMs' vast knowledge and adaptive capabilities, we provide a forward-looking overview of potential improvements LLMs can bring to EC, focusing on the algorithms themselves, population design, and additional enhancements. This presents a promising direction for future research at the intersection of LLMs and EC.