AI and the World's Hard Problems · Theoretical computer science · Nature Machine Intelligence · 2026-10-01
Large language models discover complementary heuristics for combinatorial optimization
Combinatorial optimization underpins decisions in manufacturing, logistics and energy, but designing heuristics for each new variant takes expert effort over months, and single-pass LLM code generation often fails. LACE splits algorithm design into schemas, a tool library and a heuristic portfolio, then evolves complementary specialist heuristics within runtime limits. Across 36 classical CO-Bench problems it averaged 0.945, versus 0.870 for the strongest prior LLM-based method and 0.571 for direct prompting.