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An open-source Python package implementing the Artificial Bee Colony (ABC) algorithm, a population-based optimization method inspired by the foraging behavior of honeybee swarms and designed to solve complex optimization problems efficiently.

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BeeOptimal

A Python implementation of the Artificial Bee Colony (ABC) optimization algorithm
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About

BeeOptimal is an open-source Python package that implements the Artificial Bee Colony (ABC) algorithm, a population-based optimization method inspired by the foraging behavior of honeybee swarms and designed to solve complex optimization problems efficiently. Whether you are tackling high-dimensional search spaces, multi-modal objective functions, or simply need a reliable optimizer, BeeOptimal offers a user-friendly and customizable solution for your needs.

Installation

Before installing the package, make sure you have Python 3.12 or higher installed on your system. In case you want to avoid any conflicts with your system's Python packages, you might want to create (and activate) a dedicated virtual environment:

python -m venv /path/to/beeoptimal_env
source /path/to/beeoptimal_env/bin/activate

Installing via PIP

You can install the package from the Python Package Index (PyPI) via pip:

pip install beeoptimal

Installing from source

  1. Clone the repository:

    git clone https://github.com/giuliofantuzzi/BeeOptimal.git
  2. Move into the repository directory and install the package with:

    cd BeeOptimal/
    pip install .

Optional Dependencies

In addition to the core functionalities, this package offers optional dependencies for specific use cases.

To build and work with the documentation, you can install the package with the docs extra:

pip install beeoptimal[docs]

To use the tutorials and their required dependencies, install the package with the tutorials extra:

pip install beeoptimal[tutorials]

To install both the documentation and the tutorials, you can use directly:

pip install beeoptimal[docs,tutorials]

Note

The same syntax can be followed when installing from source. Moreover, if you're using the zsh shell, you will need to wrap the extras in quotes to prevent conflicts with shell globbing (unquoted square brackets ([ ]) are used for pattern matching in zsh).

About

An open-source Python package implementing the Artificial Bee Colony (ABC) algorithm, a population-based optimization method inspired by the foraging behavior of honeybee swarms and designed to solve complex optimization problems efficiently.

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