Add dataset card README with YAML metadata

README.md

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+---
+license: mit
+language:
+  - en
+tags:
+  - job-shop-scheduling
+  - operations-research
+  - scheduling
+  - combinatorial-optimization
+  - benchmark
+  - multi-agent
+  - planning
+task_categories:
+  - other
+size_categories:
+  - 10M<n<100M
+pretty_name: REALM-Bench JSSP
+dataset_info:
+  features:
+    - name: tier
+      dtype: string
+    - name: instances
+      dtype: string
+  config_name: default
+  splits:
+    - name: J1
+      num_examples: 109
+    - name: J2
+      num_examples: 109
+    - name: J3
+      num_examples: 100
+    - name: J4
+      num_examples: 100
+---
+
+# REALM-Bench — Job Shop Scheduling (JSSP) Dataset
+
+This Hugging Face dataset hosts the **clean JSSP benchmark** from [REALM-Bench](https://github.com/genglongling/REALM-Bench): a real-world planning benchmark for LLMs and multi-agent systems ([paper](https://arxiv.org/abs/2502.18836)).
+
+All instances use a **single unified JSON schema**, organized into four tiers (**J1–J4**) as four files under `JSSP/`.
+
+## Dataset files
+
+| File | Tier | Instances | Description |
+|------|------|-----------|-------------|
+| [`JSSP/J1.json`](JSSP/J1.json) | J1 | 109 | Static benchmarks (DMU, TA, ABZ, SWV, YN) |
+| [`JSSP/J2.json`](JSSP/J2.json) | J2 | 109 | J1 instances + dynamic disruptions |
+| [`JSSP/J3.json`](JSSP/J3.json) | J3 | 100 | Large-scale static (200 jobs × 50 machines) |
+| [`JSSP/J4.json`](JSSP/J4.json) | J4 | 100 | Large-scale + multiple disruptions |
+
+**Total: 418 job-shop scheduling instances**
+
+## Problem tiers
+
+- **J1** — Classic static JSSP from standard OR benchmarks (minimize makespan).
+- **J2** — Same problems as J1 with disruptions (machine breakdown, power outage, supply delay, etc.); tests reactive replanning.
+- **J3** — Industry-scale static instances (larger job and machine counts).
+- **J4** — J3 scale with multiple simultaneous disruptions; highest difficulty tier.
+
+## Data format
+
+Each `J*.json` file has this structure:
+
+```json
+{
+  "tier": "J1",
+  "format_version": "1.0",
+  "description": "Static JSSP benchmarks (DMU, TA, ABZ, SWV, YN)",
+  "objective": "minimize_makespan",
+  "num_instances": 109,
+  "instances": [
+    {
+      "instance_id": "rcmax_50_20_9",
+      "tier": "J1",
+      "num_jobs": 50,
+      "num_machines": 20,
+      "jobs": [
+        [
+          {"operation": 1, "machine": 19, "processing_time": 64},
+          {"operation": 2, "machine": 16, "processing_time": 34}
+        ]
+      ],
+      "disruptions": [],
+      "metadata": {
+        "source_file": "DMU/rcmax_50_20_9.txt",
+        "benchmark": "DMU",
+        "objective": "minimize_makespan"
+      }
+    }
+  ]
+}
+```
+
+- **jobs** — Ordered operations per job; **machine** is 1-based; **processing_time** is a positive integer.
+- **disruptions** — Empty for J1/J3; list of events for J2/J4.
+
+See [`JSSP/README.md`](JSSP/README.md) for additional field notes.
+
+## Usage
+
+### Download with `huggingface_hub`
+
+```python
+from huggingface_hub import hf_hub_download
+import json
+
+path = hf_hub_download(
+    repo_id="GloriaGeng/REALM-Bench",
+    filename="JSSP/J1.json",
+    repo_type="dataset",
+)
+with open(path) as f:
+    data = json.load(f)
+
+print(f"Tier {data['tier']}: {data['num_instances']} instances")
+for inst in data["instances"][:3]:
+    print(inst["instance_id"], inst["num_jobs"], inst["num_machines"])
+```
+
+### Load all tiers
+
+```python
+from huggingface_hub import hf_hub_download
+import json
+
+for tier in ("J1", "J2", "J3", "J4"):
+    path = hf_hub_download("GloriaGeng/REALM-Bench", f"JSSP/{tier}.json", repo_type="dataset")
+    with open(path) as f:
+        d = json.load(f)
+    print(tier, d["num_instances"], "instances,", d["objective"])
+```
+
+### Clone the dataset
+
+```bash
+git clone https://huggingface.co/datasets/GloriaGeng/REALM-Bench
+```
+
+## Benchmark families (J1 / J2)
+
+| Family | Typical size | Source |
+|--------|----------------|--------|
+| DMU | 20×15 – 50×20 | Demirkol, Mehta, Uzsoy |
+| TA | 15×15 – 100×20 | Taillard |
+| ABZ | 20×15 | Adams, Balas, Zawack |
+| SWV | 20×10 – 50×10 | Storer, Vaccari, Van de Velde |
+| YN | 20×20 | Yamada, Nakano |
+
+## Citation
+
+If you use this dataset, please cite REALM-Bench:
+
+```bibtex
+@article{realm-bench2025,
+  title={REALM-Bench: A Real-World Planning Benchmark for LLMs and Multi-Agent Systems},
+  author={},
+  journal={arXiv preprint arXiv:2502.18836},
+  year={2025}
+}
+```
+
+## Links
+
+- **GitHub:** https://github.com/genglongling/REALM-Bench  
+- **Paper:** https://arxiv.org/abs/2502.18836  
+- **JSSP subfolder docs:** [JSSP/README.md](JSSP/README.md)
+
+## License
+
+Released under the MIT License. Benchmark instance data follows the licensing of the original sources (OR-Library, Taillard, etc.) where applicable.