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October 20, 2025Open Access

Large Language Model-Driven Surrogate-Assisted Evolutionary Algorithm for Expensive Optimization

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This novel algorithm combines large language models with surrogate-assisted evolutionary techniques, suggesting efficient optimization solutions.

LLM-SAEA demonstrates improved optimization performance in costly tasks, outperforming state-of-the-art algorithms.
The approach utilizes large language models to dynamically select surrogate models and infill sampling criteria.
A collaboration-of-experts framework enables effective scoring and decision-making in the optimization process.
Experiments across standard test cases validate the method's efficiency and adaptability to various optimization scenarios.

Xie et al. (2025) studied this question.

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October 20, 2025Open Access

View Full Paper

Ask AI

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Authors

This novel algorithm combines large language models with surrogate-assisted evolutionary techniques, suggesting efficient optimization solutions.

LLM-SAEA demonstrates improved optimization performance in costly tasks, outperforming state-of-the-art algorithms.
The approach utilizes large language models to dynamically select surrogate models and infill sampling criteria.
A collaboration-of-experts framework enables effective scoring and decision-making in the optimization process.
Experiments across standard test cases validate the method's efficiency and adaptability to various optimization scenarios.

Xie et al. (2025) studied this question.

View Full Paper

Ask AI

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