LLM-Guided Heuristic Design¶
catalog/production_agv_scheduling is the companion package for
LLM-Guided Heuristic Design from Simulation Traces.
It owns one general Method—process-aware-llm-heuristic-design—and uses dynamic
production and AGV scheduling as its full reference application.
The Method contains no production-specific imports. Everything domain-specific arrives from the selected Environment:
| The Method needs | Environment declaration |
|---|---|
| Editable policy files | candidate.files.editable and candidate.files.allow |
| Policy and snapshot contract | methodContext.instructions |
| Baseline files, domain description, trace schema, replay settings | methodContext.references |
| Entrypoint and safety checks | policyValidation |
| Deterministic diagnostic replay | exact_seed_replay capability |
This boundary is what lets the same Method optimize the AGV scheduler, a DEVS-Gen generated dispatch policy, or another compatible executable policy.
How the search works¶
- Evaluate the Environment's baseline policy over repeated seeded simulations.
- Replay the incumbent's worst seed into a bounded SQLite event trace.
- Ask a manager model to diagnose bottlenecks and propose revision plans.
- Let parallel editor models produce complete policy files.
- Validate, evaluate, and retain only improvements.
The simulator remains fixed during each trial. LLM revision happens between evaluation batches, so every Candidate is a retained executable policy that can be inspected and replayed.
Run the paper application¶
The quick smoke uses the initial policy and requires no model call:
uv run optpilot package validate catalog/production_agv_scheduling --check-source
uv run optpilot run catalog/production_agv_scheduling/studies/smoke.yaml \
--package-root catalog/production_agv_scheduling
The paper-style LLM study needs OPENROUTER_API_KEY:
uv run optpilot run \
catalog/production_agv_scheduling/studies/process_aware_llm.yaml \
--package-root catalog/production_agv_scheduling
The package also includes exhaustive rule-grid, genetic-algorithm, differential-evolution, and particle-swarm baselines evaluated by the same Environment and metric contract.
Pair it with another package¶
In Studio, select a compatible file-Candidate Environment—such as DEVS-Gen's
dispatch-station—then select Trace-guided policy design (language model).
Compatibility is decided from declarations, not package names. Save the pairing
as a Run setup and launch it normally.
See Generate and Optimize for the end-to-end DEVS-Gen composition and Candidate Contracts when adapting your own simulator.