LLM4AD: A Platform for Algorithm Design with Large Language Model

Fei Liu; Rui Zhang; Zhuoliang Xie; Rui Sun; Kai Li; Qinglong Hu; Ping Guo; Xi Lin; Xialiang Tong; Mingxuan Yuan; Zhenkun Wang; Zhichao Lu; Qingfu Zhang

arXiv · 2412.17287

LLM4AD: A Platform for Algorithm Design with Large Language Model

Fei Liu·Rui Zhang·Zhuoliang Xie·Rui Sun·Kai Li·Qinglong Hu·Ping Guo·Xi Lin·Xialiang Tong·Mingxuan Yuan·Zhenkun Wang·Zhichao Lu·Qingfu Zhang

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Abstract

We introduce LLM4AD, a unified Python platform for algorithm design (AD) with large language models (LLMs). LLM4AD is a generic framework with modularized blocks for search methods, algorithm design tasks, and LLM interface. The platform integrates numerous key methods and supports a wide range of algorithm design tasks across various domains including optimization, machine learning, and scientific discovery. We have also designed a unified evaluation sandbox to ensure a secure and robust assessment of algorithms. Additionally, we have compiled a comprehensive suite of support resources, including tutorials, examples, a user manual, online resources, and a dedicated graphical user interface (GUI) to enhance the usage of LLM4AD. We believe this platform will serve as a valuable tool for fostering future development in the merging research direction of LLM-assisted algorithm design.

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BibTeX RIS

Fei Liu, Rui Zhang, Zhuoliang Xie, Rui Sun, Kai Li, Qinglong Hu, Ping Guo, Xi Lin, Xialiang Tong, Mingxuan Yuan, Zhenkun Wang, Zhichao Lu, Qingfu Zhang. 2024-12-23. LLM4AD: A Platform for Algorithm Design with Large Language Model. https://arxiv.org/abs/2412.17287

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