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A Python library that integrates **Cellular Genetic Algorithm (Cellular GA)** with **Biased Random-Key Genetic Algorithm (BRKGA)** to enhance optimization capabilities.

Project description

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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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