Multi-Objective Bayesian Optimization

• Python 3.7
• numpy 1.16
• matplotlib 3.0
• scikit-learn 0.22
• deap 1.3
• scipy 1.1

• Clone this repo to your local machine using https://github.com/ppgaluzio/MOBOpt.git
• Run python3 setup.py install
• Using pip pip3 install https://github.com/ppgaluzio/MOBOpt/archive/master.zip

Check wiki for basic usage and documentation

Files PrintFront.py and Analisa.py, in the scripts folder, are examples of how to analyze the output of the method

To cite MOBOpt, please refer to our paper

@article{GALUZIO2020100520,
title = "MOBOpt — multi-objective Bayesian optimization",
journal = "SoftwareX",
volume = "12",
pages = "100520",
year = "2020",
issn = "2352-7110",
doi = "https://doi.org/10.1016/j.softx.2020.100520",
url = "http://www.sciencedirect.com/science/article/pii/S2352711020300911",
author = "Paulo Paneque Galuzio and Emerson Hochsteiner [de Vasconcelos Segundo] and Leandro dos Santos Coelho and Viviana Cocco Mariani"
}

For the actual version described in the publication, refer to release v1.0