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Evolving Parallel Algorithm Portfolios via Potential-Aware Instance Generation with LLMs

arXiv cs.AI · 6d ago Cached

This paper introduces PIAC, a framework that improves LLM-based automatic construction of parallel algorithm portfolios by using a potential-gain metric that eliminates the need for reference solutions and by leveraging LLMs to generate diverse instance mutators. It consistently outperforms existing LLM-ACP baselines on TSP and CVRP, achieving up to 19.76% relative improvement.

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