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Project description

OPT-LAB

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

Overview

OPT-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 source (development mode).

  1. Clone the repository
git clone https://github.com/DawnEver/opt-lab.git
cd opt-lab
  1. Create and activate a virtual environment, uv is recommanded:
uv venv
# or use venv
pip -m venv .venv
  1. 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.

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