LLM-guided program evolution improves 10 best-known circle-packing solutions (Packomania csqv, N=101-114) [R]

Excerpt

I used an LLM to iteratively evolve an optimization algorithm rather than solve the packing directly. Starting from a simple seed solver, the LLM proposes algorithmic changes guided by a scoreboard of results and a history of prior attempts, and each candidate is scored by an independent verifier so improvements are kept and failures discarded. On the Packomania csqv benchmark it improved the best-known sum-of-radii for 10 values of N from 101 to 114, by 2.4 to 5.4%, in 15 iterations. Total LLM