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---
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license: mit
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task_categories:
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- reinforcement-learning
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tags:
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- operational
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size_categories:
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- 10K<n<100K
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---
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# VRP Benchmarks |
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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. |
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## Overview |
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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. |
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## Key Features |
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- Realistic data distributions |
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- Varied problem instances |
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- Comprehensive metadata |
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- Easy integration with popular VRP solvers |
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## Dataset |
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Our dataset is generated to closely resemble real-life scenarios. It includes: |
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- Customer locations |
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- Demand quantities |
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- Time windows |
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- Vehicle capacities |
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- Depot locations |
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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. |
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## Usage |
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To use this benchmark: |
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1. Clone the repository: |
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``` |
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git clone https://github.com/ahmedheakl/vrp-benchmarks.git |
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``` |
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2. Install the required dependencies (list them here or refer to a requirements file) |
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3. Load the dataset using your preferred VRP solver or algorithm |
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4. Run your experiments and compare results with other solutions |
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## Citation |
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If you use this benchmark in your research, please cite it as follows: |
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``` |
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[Add citation information here] |
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``` |
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## License |
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This project is licensed under the [MIT License] - see the [LICENSE.md](LICENSE.md) file for details. |
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## Contact |
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For questions or feedback, please open an issue in this repository or contact [Ahmed Heakl] at [[email protected]]. |
