Improve model card: Add pipeline tag, paper link, abstract, code, and usage
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nielsr
HF Staff
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README.md
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license: mit
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# RouteFinder
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---
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license: mit
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pipeline_tag: reinforcement-learning
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---
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# RouteFinder: Towards Foundation Models for Vehicle Routing Problems
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This repository hosts the model checkpoints for **RouteFinder**, a comprehensive foundation model framework designed to tackle various Vehicle Routing Problem (VRP) variants, as presented in the paper [RouteFinder: Towards Foundation Models for Vehicle Routing Problems](https://huggingface.co/papers/2406.15007).
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## Abstract
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This paper introduces RouteFinder, a comprehensive foundation model framework to tackle different Vehicle Routing Problem (VRP) variants. Our core idea is that a foundation model for VRPs should be able to represent variants by treating each as a subset of a generalized problem equipped with different attributes. We propose a unified VRP environment capable of efficiently handling any combination of these attributes. The RouteFinder model leverages a modern transformer-based encoder and global attribute embeddings to improve task representation. Additionally, we introduce two reinforcement learning techniques to enhance multi-task performance: mixed batch training, which enables training on different variants at once, and multi-variant reward normalization to balance different reward scales. Finally, we propose efficient adapter layers that enable fine-tuning for new variants with unseen attributes. Extensive experiments on 48 VRP variants show RouteFinder outperforms recent state-of-the-art learning methods. Our code is publicly available at this https URL .
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## Code
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The official code repository is available on GitHub: [https://github.com/ai4co/routefinder](https://github.com/ai4co/routefinder)
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## Quickstart
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### Installation
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We recommend using [uv](https://github.com/astral-sh/uv) (Python package manager) to manage dependencies:
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```bash
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uv venv --python 3.12 # create a new virtual environment
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source .venv/bin/activate # activate the virtual environment
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uv sync --all-extras # for all dependencies
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```
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This project is also compatible with `pip install -e .`.
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### Download data and checkpoints
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To download the data and checkpoints from HuggingFace automatically, you can use:
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```bash
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python scripts/download_hf.py
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```
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### Running
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We recommend exploring [this quickstart notebook](https://github.com/ai4co/routefinder/blob/main/examples/1.quickstart.ipynb) to get started with the `RouteFinder` codebase!
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The main runner (example here of main baseline) can be called via:
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```bash
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python run.py experiment=main/rf/rf-transformer-100
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```
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You may change the experiment by using the `experiment=YOUR_EXP`, with the path under [`configs/experiment`](https://github.com/ai4co/routefinder/tree/main/configs/experiment) directory.
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## Citation
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If you find RouteFinder valuable for your research or applied projects, please cite our paper:
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```bibtex
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@article{
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berto2025routefinder,
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title={{RouteFinder: Towards Foundation Models for Vehicle Routing Problems}},
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author={Federico Berto and Chuanbo Hua and Nayeli Gast Zepeda and Andr{\'e} Hottung and Niels Wouda and Leon Lan and Junyoung Park and Kevin Tierney and Jinkyoo Park},
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journal={Transactions on Machine Learning Research},
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issn={2835-8856},
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year={2025},
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url={https://openreview.net/forum?id=QzGLoaOPiY},
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}
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```
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