ES-AHD: An Evolution Strategy Framework for Automatic Heuristic Design
In this paper, we introduce ES-AHD, a novel framework that fundamentally integrates Evolution Strategy (ES) into Large Language Model (LLM)-driven Automatic Heuristic Design (AHD). Existing evolutionary approaches predominantly rely on random, individual-level mutation, leading to blind search and an imbalance between exploration and exploitation. To address these issues, ES-AHD introduces two core mechanisms. First, Semantic Recombination via LLMs discards traditional point-to-point reproduction. By leveraging the LLM's contextual reasoning to explicitly extract core insights from top-performing individuals, the algorithm establishes a promising semantic search direction. This transforms...
| Authors | Yutao Lai, Kezhao Lai, Hai-Lin Liu et al. |
|---|---|
| Primary category | cs.NE |
| Published | 26 August 2026 |
| Last updated at source | 26 August 2026 |
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