MOBOpt
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Multi-objective Bayesian optimization
MOBOpt
Multi-Objective Bayesian Optimization
Prerequisites
- Python 3.7
- numpy 1.16
- matplotlib 3.0
- scikit-learn 0.22
- deap 1.3
- scipy 1.1
Instalation
- 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
Usage
Check wiki for basic usage and documentation
Analysis
Files PrintFront.py and Analisa.py, in the scripts folder, are
examples of how to analyze the output of the method
Cite
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