articleACM Computing SurveysJan 12, 2026HYBRID OA

A Systematic Survey on Large Language Models for Algorithm Design

FLFei LiuYYYiming YaoPGPing GuoZYZhiyuan YangXLXi Lin

City University of Hong Kong · Huawei Technologies (Sweden) · +4 more institutions

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Abstract

Algorithm design is crucial for effective problem-solving across various domains. The advent of Large Language Models (LLMs) has notably enhanced the automation and innovation within this field, offering new perspectives and promising solutions. In just a few years, this integration has yielded remarkable progress in areas ranging from combinatorial optimization to scientific discovery. Despite this rapid expansion, a holistic understanding of the field is hindered by the lack of a systematic review, as existing surveys either remain limited to narrow sub-fields or with different objectives. This article seeks to provide a systematic review of algorithm design with LLMs. We introduce a taxonomy that…

Citation impact

5
total citations
FWCI
144.10
Percentile
99%
References
32
Citations per year

Authors

12

Topics & keywords

Keywords
  • Taxonomy (biology)
  • Pipeline (software)
  • Key (lock)
  • Field (mathematics)
  • Automation
  • Open research
  • Systematic review
UN Sustainable Development Goals
  • Industry, innovation and infrastructure
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