Metadata-Version: 2.1
Name: pymoo
Version: 0.4.2
Summary: Multi-Objective Optimization in Python
Home-page: https://pymoo.org
Author: Julian Blank
Author-email: blankjul@egr.msu.edu
License: Apache License 2.0
Description: .. |travis| image:: https://travis-ci.com/msu-coinlab/pymoo.svg?branch=master
           :alt: build status
           :target: https://travis-ci.com/msu-coinlab/pymoo
        
        .. |python| image:: https://img.shields.io/badge/python-3.6-blue.svg
           :alt: python 3.6
        
        .. |license| image:: https://img.shields.io/badge/license-apache-orange.svg
           :alt: license apache
           :target: https://www.apache.org/licenses/LICENSE-2.0
        
        
        .. |logo| image:: https://github.com/msu-coinlab/pymoo//raw/master/doc/source/_theme/custom_theme/static/img/pymoo_banner_github.png
          :target: https://pymoo.org
          :alt: pymoo
        
        
        .. |animation| image:: https://github.com/msu-coinlab/pymoo//raw/master/doc/source/_theme/custom_theme/static/img/animation.gif
          :target: https://pymoo.org
          :alt: pymoo
        
        
        .. _Github: https://github.com/msu-coinlab/pymoo
        .. _Documentation: https://www.pymoo.org/
        .. _Paper: https://arxiv.org/abs/2002.04504
        
        
        
        
        |travis| |python| |license|
        
        
        |logo|
        
        
        
        Documentation_ / Paper_ / Installation_ / Usage_ / Citation_ / Contact_
        
        
        
        pymoo: Multi-objective Optimization in Python
        ====================================================================
        
        Our open-source framework pymoo offers state of the art single- and multi-objective algorithms and many more features
        related to multi-objective optimization such as visualization and decision making.
        
        
        .. _Installation:
        
        Installation
        ********************************************************************************
        
        First, make sure you have a Python 3 environment installed. We recommend miniconda3 or anaconda3.
        
        The official release is always available at PyPi:
        
        .. code:: bash
        
            pip install -U pymoo
        
        
        For the current developer version:
        
        .. code:: bash
        
            git clone https://github.com/msu-coinlab/pymoo
            cd pymoo
            pip install .
        
        
        Since for speedup some of the modules are also available compiled you can double check
        if the compilation worked. When executing the command be sure not already being in the local pymoo
        directory because otherwise not the in site-packages installed version will be used.
        
        .. code:: bash
        
            python -c "from pymoo.util.function_loader import is_compiled;print('Compiled Extensions: ', is_compiled())"
        
        
        .. _Usage:
        
        Usage
        ********************************************************************************
        
        We refer here to our documentation for all the details.
        However, for instance executing NSGA2:
        
        .. code:: python
        
            
            from pymoo.algorithms.nsga2 import NSGA2
            from pymoo.factory import get_problem
            from pymoo.optimize import minimize
            from pymoo.visualization.scatter import Scatter
        
            problem = get_problem("zdt1")
        
            algorithm = NSGA2(pop_size=100)
        
            res = minimize(problem,
                           algorithm,
                           ('n_gen', 200),
                           seed=1,
                           verbose=False)
        
            plot = Scatter()
            plot.add(problem.pareto_front(), plot_type="line", color="black", alpha=0.7)
            plot.add(res.F, color="red")
            plot.show()
        
        
        
        A representative run of NSGA2 looks as follows:
        
        |animation|
        
        
        
        
        .. _Citation:
        
        Citation
        ********************************************************************************
        
        We are currently working on a journal publication for *pymoo*.
        Meanwhile, if you have used our framework for research purposes, please cite us with:
        
        ::
        
            @ARTICLE{pymoo,
                author={J. {Blank} and K. {Deb}},
                journal={IEEE Access},
                title={Pymoo: Multi-Objective Optimization in Python},
                year={2020},
                volume={8},
                number={},
                pages={89497-89509},
            }
        
        
        
        .. _Contact:
        
        Contact
        ********************************************************************************
        
        Feel free to contact me if you have any question:
        
        | `Julian Blank <http://julianblank.com>`_  (blankjul [at] egr.msu.edu)
        | Michigan State University
        | Computational Optimization and Innovation Laboratory (COIN)
        | East Lansing, MI 48824, USA
        
        
        
        
Keywords: optimization
Platform: any
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: OS Independent
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Mathematics
Requires-Python: >=3.6
Description-Content-Type: text/x-rst
