TUIASI_OCS_TEAM11_2025

A Python framework for optimization algorithms developed by Team 11.

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Table of Contents

• Installation
• Usage
  • Running Examples
  • Developing with the Framework
• Folder Structure
• Contributing
• License

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Installation

To set up the project, follow these steps:

1. Clone the repository:

   git clone https://github.com/CatalinButacu/OCS_FRAMEWORK.git
   cd TUIASI_OCS_TEAM11_2025

2. Create a virtual environment (optional but recommended):

   python -m venv venv

3. Activate the virtual environment:

   On Windows:

   venv\Scripts\activate

   On macOS/Linux:

   source venv/bin/activate

4. Install dependencies:

   pip install -r requirements.txt

5. Install the framework in editable mode:

   pip install -e .

   This ensures that changes to the framework code are reflected immediately.

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Usage

Running Examples

To run the example scripts located in the examples folder, use the following command:

python examples/example_canonical_ga.py

Developing with the Framework

You can import the framework in your scripts like this:

from framework.algorithms.canonical_ga import CGA, CGAAdaptiveV2, CGAGreedy

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Folder Structure

TUIASI_OCS_TEAM11_2025/
├── examples/                # Example scripts sample of using library
│   └── example_canonical_ga.py
├── framework/               # Core framework code
│   ├── algorithms/          # Optimization algorithms
│   │   ├── random_search/             # Stochastic Optimization Algorithm
│   │   ├── canonical_ga/              # Classic Genetic Algorithm
│   │   ├── real_ga/                   # Real-Valued Genetic Algorithm
│   │   └── differential_evolution/    # Differential Evolution Algorithm
│   ├── benchmarks/          # Definition of benchmark functions  
│   └── utils/               # Utility functions
├── results/                 # Benchmark results
│   ├── csv/                 # CSV data
│   └── images/              # Visualizations
├── test/                    # Test integrity of framework components
├── config_test_run.py       # Change configuration of running test
├── run_benchmark.py         # Run benchmarks
├── view_results.py          # Generate visualizations
├── requirements.txt         # Project dependencies
├── setup.py                 # Package installation script
└── README.md                # This file

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Results

Benchmark results, including CSV files and visualizations, are stored in the following location:

🔗 Results Folder

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Contributing

We welcome contributions! Please follow these steps:

1. Fork the repository.
2. Create a new branch for your feature or bugfix:

   git checkout -b feature/your-feature-name

3. Commit your changes:

   git commit -m "Add your message here"

4. Push to the branch:

   git push origin feature/your-feature-name

5. Open a pull request.

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License

This project is licensed under the MIT License. See the LICENSE file for details.