Skip to main content

The python version reference vector guided evolutionary algorithm.

Project description

desdeo-emo

Binder

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 and NSGA-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

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.

Citation

If you decide to use DESDEO is any of your works or research, we would appreciate you citing the appropiate paper published in IEEE Access (open access).

Project details


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-1.5.0.tar.gz (64.0 kB view details)

Uploaded Source

Built Distribution

desdeo_emo-1.5.0-py3-none-any.whl (100.3 kB view details)

Uploaded Python 3

File details

Details for the file desdeo_emo-1.5.0.tar.gz.

File metadata

  • Download URL: desdeo_emo-1.5.0.tar.gz
  • Upload date:
  • Size: 64.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.3.2 CPython/3.10.9 Linux/5.15.94-1-MANJARO

File hashes

Hashes for desdeo_emo-1.5.0.tar.gz
Algorithm Hash digest
SHA256 a888cb47de85abd0a2e1ad50c1ae1437b0cc6393c72a64eb2f812c813b8b19b4
MD5 40ac6ee67c2158631098da0a867e62f5
BLAKE2b-256 28da933debb996b94b5865ae407dee0cee4248be590fd8067ab2cca0bd8f2a46

See more details on using hashes here.

File details

Details for the file desdeo_emo-1.5.0-py3-none-any.whl.

File metadata

  • Download URL: desdeo_emo-1.5.0-py3-none-any.whl
  • Upload date:
  • Size: 100.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.3.2 CPython/3.10.9 Linux/5.15.94-1-MANJARO

File hashes

Hashes for desdeo_emo-1.5.0-py3-none-any.whl
Algorithm Hash digest
SHA256 e646c517b897e6f91937b76c15680a4ddfc7ca1fcc196ae554e5fb521d329c01
MD5 a343157144eac4b800225368e862a584
BLAKE2b-256 1920b79e7e3bde89c984e07f19ed8c33aa99553c60ece75c8fb3d85f8712ddb6

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page