optimi-lab 0.1.1

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Optimi-Lab

An extensible optimization toolbox for prototyping evolutionary and surrogate-based optimization workflows.

Overview

Optimi-Lab provides implementations and utilities for evolutionary algorithms, surrogate models, and sensitivity analysis. It is intended for researchers and practitioners who need a lightweight framework for experiments and benchmarking.

Key Features

• Multi-objective and single-objective optimization algorithms
• Surrogate modeling utilities and model selection helpers
• Built-in logging and experiment output management
• Examples and tests for reproducibility

Installation

Recommended: install from pypi

uv pip install optimi-lab # use uv

or

pip install optimi-lab

Install from source (development mode).

1. Clone the repository

git clone https://github.com/DawnEver/optimi-lab.git
cd optimi-lab

2. Create and activate a virtual environment, uv is recommanded:

uv venv
# or use venv
pip -m venv .venv

3. Install the package

uv pip install -e . # for normal user
uv pip install -e ".[dev]" # for developer

Usage

Typical steps:

1. Define an objective function.
2. Configure an optimizer (algorithm, population size, termination criteria).
3. Run the optimizer and inspect outputs in the output/ directory.

See examples/ for concrete usage examples.

Contributing

Contributions are welcome — please open an issue to discuss large changes before submitting a pull request. Add tests for new features and follow the existing code style.

License

This project is licensed under the Apache License 2.0 — see the LICENSE file for details.

Contact

For questions or collaboration, open an issue or contact the maintainers through the repository.