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.# Offline_IMOEA_Framework