---
license: cc-by-4.0
language:
- en
pretty_name: FrontierOR Benchmark
size_categories:
- n<1K
task_categories:
- other
tags:
- operations-research
- optimization
- mixed-integer-programming
- gurobi
- benchmark
- llm-for-or
configs:
- config_name: meta
data_files: metadata/paper_meta_info.json
---
# FrontierOR Benchmark
A benchmark of **180 literature-grounded OR tasks**, each packaged as a
self-contained reproducible unit: natural-language problem description,
mathematical formulation, reference Gurobi implementation, test instances,
reference solutions, and an automated feasibility checker.
Designed for evaluating LLMs on the end-to-end task of turning a research
paper's OR problem into runnable, verifiably-correct optimization code.
## **🎯 FrontierOR-v1 is released!**
**FrontierOR-v1 was updated on 2026-09-27.** This important dataset update consolidates the canonical 180-task collection, Gurobi references, hard-set split metadata, feasibility checkers, and task-instance artifacts. For detailed fixes and compatibility notes, see [`RELEASE_NOTES.md`](RELEASE_NOTES.md).
## Layout
| Path | Purpose |
| --- | --- |
| `README.md` | Dataset overview and loading instructions |
| `RELEASE_NOTES.md` | Detailed FrontierOR-v1 update notes |
| `CASE_IDS.txt` | Canonical task id list |
| `LICENSE.md` | Dataset license |
| `metadata/` | Paper metadata, Gurobi reference summaries, and benchmark split metadata |
| `metadata/paper_meta_info.json` | Metadata for all 180 canonical papers, including optimization direction |
| `metadata/gurobi_references.parquet` / `.csv.gz` | Canonical Gurobi objectives, runtimes, statuses, and related reference fields |
| `metadata/hardset/` | Hard-set ids, ranking inputs, methodology, and reproduction script |
| `tasks//` | Self-contained task package for one paper |
## What's in each task folder
| File / dir | Purpose |
| --- | --- |
| `problem_description.txt` | Natural-language problem statement |
| `mathematical_formulation.md` | Mathematical model (variables, constraints, objective) |
| `gurobi_code.py` | Reference Gurobi implementation |
| `feasibility_check.py` | Automated solution validator |
| `solution_logger.py` | Utility for serializing solutions |
| `instance_schema.json` | JSON schema for input instances |
| `solution_schema.json` | JSON schema for solutions |
| `instance/` | Six benchmark instances: `tiny_instance.json` and `large_instance_1.json` through `large_instance_5.json` |
| `gurobi_solution/` | Reference Gurobi solutions for the tiny and five large instances |
| `gurobi_solution_log/` | Anytime incumbent objective trajectories from the reference Gurobi runs |
| `gurobi_feasi_result/` | Feasibility-check outputs for the reference Gurobi solutions |
| `solverless_models/` | Optional task-local assets for checkers that need solver-independent validation models |
## Loading the metadata
```python
from datasets import load_dataset
meta = load_dataset("frontieror/FrontierOR", "meta", split="train")
print(meta[0])
```
For the per-paper instance / solution data, clone or download the full
repository — the structure is intentionally a file tree, not a flat HF
dataset, because each paper is its own reproducible package under
`tasks//`.
```bash
hf download frontieror/FrontierOR --repo-type dataset --local-dir frontier-or
```
To update an existing local copy without downloading everything from scratch,
rerun the same command; unchanged files are reused from the Hugging Face cache
and only missing or changed files are fetched.
```bash
hf download frontieror/FrontierOR --repo-type dataset --local-dir frontier-or
```
If your local copy was created by `git clone`, update it with:
```bash
cd frontier-or
git pull
git lfs pull
```
When upgrading from an older snapshot, note that files deleted upstream may
remain in an existing `--local-dir` checkout. Remove stale top-level files
manually if present, or refresh from a clean directory when exact directory
parity is required.