The python version reference vector guided evolutionary algorithm.
Project description
desdeo-emo
The evolutionary algorithms package within the desdeo
framework.
Code for the SoftwareX paper can be found in this notebook.
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
- Constraint handling using
RVEA
- IOPIS optimization using
RVEA
andNSGA-III
Currently NOT supported:
- Binary and integer variables.
To test the code, open the binder link and read example.ipynb.
Read the documentation here
Requirements
- Python 3.7 or newer.
- 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.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
desdeo_emo-1.3.2.tar.gz
(53.0 kB
view hashes)
Built Distribution
desdeo_emo-1.3.2-py3-none-any.whl
(82.4 kB
view hashes)
Close
Hashes for desdeo_emo-1.3.2-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 12292451e60ca83d5e5d4a263b5c059ea4376a8a016a4604bd026146615207ca |
|
MD5 | 0f4ed6309eac246e8b11d75901c9a4ef |
|
BLAKE2b-256 | 6ed36f81db365ec98ff5678ef04071707b7ad6d1880a890c03073896122fcb59 |