Summary of Large Language Model-based Evolutionary Optimizer: Reasoning with Elitism, by Shuvayan Brahmachary et al.
Large Language Model-Based Evolutionary Optimizer: Reasoning with elitism
by Shuvayan Brahmachary, Subodh M. Joshi, Aniruddha Panda, Kaushik Koneripalli, Arun Kumar Sagotra, Harshil Patel, Ankush Sharma, Ameya D. Jagtap, Kaushic Kalyanaraman
First submitted to arxiv on: 4 Mar 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary Medium Difficulty summary: This paper explores the application of Large Language Models (LLMs) as zero-shot optimizers in various scenarios, including multi-objective and high-dimensional problems. The authors introduce a novel population-based optimization method called LEO, which leverages LLMs’ capabilities to solve benchmark and industrial engineering problems such as supersonic nozzle shape optimization, heat transfer, and windfarm layout optimization. The results show that LLMs can yield comparable performance to state-of-the-art methods while highlighting the need for careful handling due to their imaginative nature and propensity to hallucinate. Practical guidelines are provided to obtain reliable answers from LLMs, and potential research directions are discussed. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Low Difficulty summary: This paper is about using special computers called Large Language Models (LLMs) to solve problems that involve finding the best solution. The authors created a new way of doing this, called LEO, which uses LLMs to find the best answer in different types of problems. They tested it on some real-world problems and found that it worked well, but they also warned that LLMs can sometimes make mistakes because they are very good at making up creative answers. The paper suggests ways to get reliable answers from LLMs and proposes new areas for research. |
Keywords
» Artificial intelligence » Optimization » Zero shot
