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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).
- Clone the repository
git clone https://github.com/DawnEver/opt-lab.git
cd opt-lab
- Create and activate a virtual environment, uv is recommanded:
uv venv
# or use venv
pip -m venv .venv
- Install the package
uv pip install -e . # for normal user
uv pip install -e ".[dev]" # for developer
Usage
Typical steps:
- Define an objective function.
- Configure an optimizer (algorithm, population size, termination criteria).
- 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.
Project details
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