A Python library that integrates **Cellular Genetic Algorithm (Cellular GA)** with **Biased Random-Key Genetic Algorithm (BRKGA)** to enhance optimization capabilities.
Project description
CelluKeyGA
🚀 CelluKeyGA is a Python library that integrates Cellular Genetic Algorithm (Cellular GA) with Biased Random-Key Genetic Algorithm (BRKGA) to enhance optimization capabilities. This project aims to provide a flexible and efficient evolutionary computing framework for solving complex optimization problems.
🔹 Features
- Combines Cellular GA and BRKGA for improved solution diversity and performance.
- Designed for solving combinatorial and continuous optimization problems.
- Modular and extensible structure for easy customization.
🛠️ Applications
CelluKeyGA can be applied in various domains, including:
- ✅ Scheduling and routing problems.
- ✅ Machine learning hyperparameter optimization.
- ✅ Engineering design optimization.
- ✅ Any problem requiring robust metaheuristic search strategies.
📦 Installation
pip install cellukeyga
🚀 Getting Started
from cellukeyga import CelluKeyGA
# Example usage
ckga = CelluKeyGA()
ckga.run()
📂 Roadmap
- Implement core algorithm.
- Add benchmark test problems.
- Provide detailed documentation.
- Integrate with pymoo.
🤝 Contributing
Contributions are welcome! Feel free to open issues and pull requests.
📜 License
MIT License (or any other license you prefer).
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