--- 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

Website   arXiv   GitHub

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.