The python version reference vector guided evolutionary algorithm.
Project description
desdeo-emo
The evolutionary algorithms package within the desdeo
framework.
Currently supported:
- Multi-objective optimization with visualization and interaction support.
- Preference is accepted as a reference point.
- Surrogate modelling (neural networks and genetic trees) evolved via EAs.
- Surrogate assisted optimization
Currently NOT supported:
- Constraint handling
The documentation is currently being worked upon
To test the code, open the binder link and read example.ipynb.
Read the documentation here
Requirements:
- Python 3.7 or up
- Poetry dependency manager: Only for developers
Installation process for normal users:
- Create a new virtual enviroment for the project
- Run:
pip install desdeo_emo
Installation process for developers:
- Download and extract the code or
git clone
- Create a new virtual environment for the project
- Run
poetry install
inside the virtual environment shell.
See the details of various algorithms in the following papers (to be updated)
R. Cheng, Y. Jin, M. Olhofer and B. Sendhoff, A Reference Vector Guided Evolutionary Algorithm for Many-objective Optimization, IEEE Transactions on Evolutionary Computation, 2016
The source code of pyrvea is implemented by Bhupinder Saini
If you have any questions about the code, please contact:
Bhupinder Saini: bhupinder.s.saini@jyu.fi
Project researcher at University of Jyväskylä.
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