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---
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]. |