Benchmark-driven AI discovers complementary optimization heuristics

A study evaluates language-model-generated heuristic portfolios on 40 combinatorial-optimization benchmarks and reports generalization to structurally new problems. Public code, data, Zenodo artifacts, and a Colab notebook strengthen reproducibility, while computational cost, robustness, and comparison fairness remain open questions.