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Status](https://img.shields.io/circleci/project/github/esa/pagmo2/master.svg?style=for-the-badge)](https://circleci.com/gh/esa/pagmo2)\n[![Build Status](https://img.shields.io/github/actions/workflow/status/esa/pagmo2/main.yml?branch=master\u0026style=for-the-badge)](https://github.com/esa/pagmo2/actions?query=workflow%3A%22GitHub+CI%22)\n[![Build Status](https://img.shields.io/travis/com/esa/pagmo2?style=for-the-badge)](https://travis-ci.com/esa/pagmo2)\n[![Code Coverage](https://img.shields.io/codecov/c/github/esa/pagmo2.svg?style=for-the-badge)](https://codecov.io/github/esa/pagmo2?branch=master)\n\n[![Anaconda-Server Badge](https://img.shields.io/conda/vn/conda-forge/pagmo.svg?style=for-the-badge)](https://anaconda.org/conda-forge/pagmo)\n\n[![Join the chat at https://gitter.im/pagmo2/Lobby](https://img.shields.io/badge/gitter-join--chat-green.svg?logo=gitter-white\u0026style=for-the-badge)](https://gitter.im/pagmo2/Lobby?utm_source=badge\u0026utm_medium=badge\u0026utm_campaign=pr-badge\u0026utm_content=badge)\n\n[![DOI](https://joss.theoj.org/papers/10.21105/joss.02338/status.svg)](https://doi.org/10.21105/joss.02338)\n[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.1045337.svg)](https://doi.org/10.5281/zenodo.1045336)\n\n**IMPORTANT NOTICE**: pygmo, the Python bindings for pagmo, have been split off into a separate\nproject, hosted [here](https://github.com/esa/pygmo2). Please update your bookmarks!\n\npagmo is a C++ scientific library for massively parallel optimization. It is built around the idea of providing\na unified interface to optimization algorithms and to optimization problems and to make their deployment in\nmassively parallel environments easy.\n\nIf you are using pagmo as part of your research, teaching, or other activities, we would be grateful if you could star\nthe repository and/or cite our work. For citation purposes, you can use the following BibTex entry, which refers\nto the [pagmo paper](https://doi.org/10.21105/joss.02338) in the Journal of Open Source Software:\n\n```bibtex\n@article{Biscani2020,\n  doi = {10.21105/joss.02338},\n  url = {https://doi.org/10.21105/joss.02338},\n  year = {2020},\n  publisher = {The Open Journal},\n  volume = {5},\n  number = {53},\n  pages = {2338},\n  author = {Francesco Biscani and Dario Izzo},\n  title = {A parallel global multiobjective framework for optimization: pagmo},\n  journal = {Journal of Open Source Software}\n}\n```\n\nThe DOI of the latest version of the software is available at [this link](https://doi.org/10.5281/zenodo.1045336).\n\nThe full documentation can be found [here](https://esa.github.io/pagmo2/).\n\nUpgrading from pagmo 1.x.x\n==========================\n\nIf you were using the old pagmo, have a look here on some technical data on what and why a completely\nnew API and code was developed: https://github.com/esa/pagmo2/wiki/From-1.x-to-2.x\n\nYou will find many tutorials in the documentation, we suggest to skim through them to\nrealize the differences. The new pagmo (version 2) should be considered (and is) as an entirely different code.\n","funding_links":[],"categories":["C++","其他_机器学习与深度学习"],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fesa%2Fpagmo2","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fesa%2Fpagmo2","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fesa%2Fpagmo2/lists"}