bbob-jax 0.4.0

BBOB Benchmark function implemented in JAX

BBOB Benchmark set for Jax

| GitHub | PyPi | Documentation |

WARNING: THIS REPOSITORY IS STILL UNDER ACTIVE DEVELOPMENT. THE API AND FUNCTIONALITY MAY CHANGE IN FUTURE RELEASES.

JAX implementation of the BBOB Benchmark functions for black-box optimization, based on the original definitions by Finck et al. (2009) [^1].

[^1]: Finck, S., Hansen, N., Ros, R., and Auger, A. (2009), Real-parameter black-box optimization benchmarking 2009: Noiseless functions definitions, INRIA.

First publication: October 17, 2025

---

Statement of need

This repository providess the original BBOB 24 noise-free, real-parameter, single-objective benchmark functions reimplemented in JAX. Originally written in C, these functions have been translated to JAX to enable automatic differentiation, just-in-time (JIT) compilation, and XLA-accelerated performance — making them ideal for research in optimization, machine learning, and evolutionary algorithms.

3D surface plots of the 24 BBOB benchmark functions.


2D contour plots of the 24 BBOB benchmark functions.

Authorship

Authors:

• Martin van der Schelling ([e-mail])

Authors afilliation:

• Delft University of Technology (Bessa Research Group)

Maintainer:

• Martin van der Schelling ([e-mail])

Maintainer afilliation:

• Delft University of Technology (Bessa Research Group)

Getting started

To install the package, use pip:

pip install bbob-jax

Community Support

If you find any issues, bugs or problems with this package, please use the GitHub issue tracker to report them.

License

Copyright (c) 2025, Martin van der Schelling

All rights reserved.

This project is licensed under the BSD 3-Clause License. See LICENSE for the full license text.