---
license: mit
task_categories:
- reinforcement-learning
tags:
- operational
size_categories:
- 10K<n<100K
---
# VRP Benchmarks

This repository contains a benchmark dataset for the Vehicle Routing Problem (VRP), designed to closely mimic real-world scenarios by replicating realistic distributions of data.

## Overview

The Vehicle Routing Problem is a complex optimization challenge in logistics and transportation. Our benchmark provides a comprehensive dataset that researchers and practitioners can use to test and compare different VRP algorithms and solutions.

## Key Features

- Realistic data distributions
- Varied problem instances
- Comprehensive metadata
- Easy integration with popular VRP solvers

## Dataset

Our dataset is generated to closely resemble real-life scenarios. It includes:

- Customer locations
- Demand quantities
- Time windows
- Vehicle capacities
- Depot locations

The data generation process takes into account various factors such as population density, traffic patterns, and typical business distributions to create a highly realistic benchmark.

## Usage

To use this benchmark:

1. Clone the repository:
   ```
   git clone https://github.com/ahmedheakl/vrp-benchmarks.git
   ```

2. Install the required dependencies (list them here or refer to a requirements file)

3. Load the dataset using your preferred VRP solver or algorithm

4. Run your experiments and compare results with other solutions


## Citation

If you use this benchmark in your research, please cite it as follows:

```
[Add citation information here]
```

## License

This project is licensed under the [MIT License] - see the [LICENSE.md](LICENSE.md) file for details.

## Contact

For questions or feedback, please open an issue in this repository or contact [Ahmed Heakl] at [ahmed.heakl@mbzuai.ac.ae].