CoupleEvo
An LLM heuristic-evolution method for problems made of several linked sub-problems, with three ways to coordinate the evolution.
The loop
- Proposes
Heuristics for each sub-problem, written by an LLM inside an evolutionary loop
- Judged by
Running the combined heuristics on instances of the coupled problem
- Steers
Sequential, iterative or integrated schedules decide which sub-problem's heuristic evolves in each generation
Headline result
On two coupled problems (inventory routing, and multi-robot multi-bay pre-marshalling) with Qwen3-coder:30b, the sequential and iterative strategies converged more stably than the integrated one. On inventory routing the mean relative gap was 0.0429 (sequential), 0.0433 (iterative), 0.0537 (integrated).
What this does not prove
Two problems and one model. The paper's own text says iterative has the smallest median on one problem while its table shows sequential lower, so read the tables, not the prose. Accepted to a GECCO 2026 workshop.
How it generalizes the harness
An evolutionary schedule over several sub-heuristics is the solver, and the evolved heuristics run without the model.
Classification
| What it proposes | Heuristic |
|---|---|
| Generative model | Qwen3-coder:30b, frozen |
| Algorithmic authority | Evaluation on coupled-problem instances |
| Feedback | Score |
| What gets updated | Population of candidates |
| When it runs | Offline, at design time |
| Validity | Empirical (measured) |
| Evidence | Experiments reported |
| Lineage | Derivative |