https://github.com/esa/pygmo2

A Python platform to perform parallel computations of optimisation tasks (global and local) via the asynchronous generalized island model.
https://github.com/esa/pygmo2

artificial-intelligence evolutionary-algorithms evolutionary-computation evolutionary-strategy island-model meta-heuristic meta-heuristics multiobjective-optimization optimization optimization-algorithms optimization-methods optimization-problem parallel-computing parallel-processing stochastic-optimization

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A Python platform to perform parallel computations of optimisation tasks (global and local) via the asynchronous generalized island model.

• Host: GitHub
• URL: https://github.com/esa/pygmo2
• Owner: esa
• License: mpl-2.0
• Created: 2020-01-07T09:22:45.000Z (about 5 years ago)
• Default Branch: master
• Last Pushed: 2024-04-04T16:04:46.000Z (10 months ago)
• Last Synced: 2024-04-14T10:15:27.854Z (9 months ago)
• Topics: artificial-intelligence, evolutionary-algorithms, evolutionary-computation, evolutionary-strategy, island-model, meta-heuristic, meta-heuristics, multiobjective-optimization, optimization, optimization-algorithms, optimization-methods, optimization-problem, parallel-computing, parallel-processing, stochastic-optimization
• Language: C++
• Homepage: https://esa.github.io/pygmo2/
• Size: 13.9 MB
• Stars: 402
• Watchers: 10
• Forks: 54
• Open Issues: 37
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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• awesome-scientific-computing - GitHub

README

        
pygmo

=====

[![Build Status](https://img.shields.io/circleci/project/github/esa/pygmo2/master.svg?style=for-the-badge)](https://circleci.com/gh/esa/pygmo2)

[![Build Status](https://img.shields.io/github/actions/workflow/status/esa/pygmo2/main.yml?branch=master&style=for-the-badge)](https://github.com/esa/pygmo2/actions?query=workflow%3A%22CI%22)

[![Anaconda-Server Badge](https://img.shields.io/conda/vn/conda-forge/pygmo.svg?style=for-the-badge)](https://anaconda.org/conda-forge/pygmo)

[![PyPI](https://img.shields.io/pypi/v/pygmo.svg?style=for-the-badge)](https://pypi.python.org/pypi/pygmo)

[![Join the chat at https://gitter.im/pagmo2/Lobby](https://img.shields.io/badge/gitter-join--chat-green.svg?logo=gitter-white&style=for-the-badge)](https://gitter.im/pagmo2/Lobby?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)

[![DOI](https://joss.theoj.org/papers/10.21105/joss.02338/status.svg)](https://doi.org/10.21105/joss.02338)

[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.1045337.svg)](https://doi.org/10.5281/zenodo.1045336)

pygmo is a scientific Python library for massively parallel optimization. It is built around the idea

of providing a unified interface to optimization algorithms and to optimization problems and to make their

deployment in massively parallel environments easy.

If you are using pygmo as part of your research, teaching, or other activities, we would be grateful if you could star

the repository and/or cite our work. For citation purposes, you can use the following BibTex entry, which refers

to the [pygmo paper](https://doi.org/10.21105/joss.02338) in the Journal of Open Source Software:

```bibtex

@article{Biscani2020,

  doi = {10.21105/joss.02338},

  url = {https://doi.org/10.21105/joss.02338},

  year = {2020},

  publisher = {The Open Journal},

  volume = {5},

  number = {53},

  pages = {2338},

  author = {Francesco Biscani and Dario Izzo},

  title = {A parallel global multiobjective framework for optimization: pagmo},

  journal = {Journal of Open Source Software}

}

```

The DOI of the latest version of the software is available at [this link](https://doi.org/10.5281/zenodo.1045336).

The full documentation can be found [here](https://esa.github.io/pygmo2/).

Upgrading from pygmo 1.x.x

==========================

If you were using the old pygmo, have a look here on some technical data on what and why a completely new API

and code was developed: https://github.com/esa/pagmo2/wiki/From-1.x-to-2.x

You will find many tutorials in the documentation, we suggest to skim through them to realize the differences.

The new pygmo (version 2) should be considered (and is) as an entirely different code.