QDEvo: A Multi-Objective Quality-Diversity Framework for Automated Heuristic Design
The integration of Large Language Models (LLMs) with evolutionary computation has emerged as a powerful paradigm for automated heuristic design in combinatorial optimization. However, existing approaches suffer from mode collapse, converging to homogeneous populations that lack semantic diversity and fail to explore the full algorithmic space. We propose Quality-Diversity Evolution (QDEvo), a multi-objective framework that integrates Quality-Diversity optimization with LLM-driven heuristic search, maintaining an unbounded archive of semantically diverse algorithms using pre-trained code embeddings and incorporating hierarchical self-reflection to guide the evolutionary process. Extensive ...
| Authors | Nam Do Khanh, Nhat Nguyen Tran Minh, Dat Pham Vu Tuan et al. |
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| Primary category | cs.NE |
| Published | 6 July 2026 |
| Last updated at source | 6 July 2026 |
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