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-1.4.2.tar.gz (63.9 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

desdeo_emo-1.4.2-py3-none-any.whl (100.6 kB view details)

Uploaded Python 3

File details

Details for the file desdeo_emo-1.4.2.tar.gz.

File metadata

  • Download URL: desdeo_emo-1.4.2.tar.gz
  • Upload date:
  • Size: 63.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.1.8 CPython/3.7.7 Windows/10

File hashes

Hashes for desdeo_emo-1.4.2.tar.gz
Algorithm Hash digest
SHA256 ca94bc8c7e1fb773dd2008df5fc268259dfcf2cf0d784070fdcc1369e2b9d1da
MD5 3dfab3ed493cebbf4e09b04bcdbaa506
BLAKE2b-256 34e11b9fd5bd8ef74616ea95bd5a3d4c3026fc35cb7b7bda631bb7ab00be0fd5

See more details on using hashes here.

File details

Details for the file desdeo_emo-1.4.2-py3-none-any.whl.

File metadata

  • Download URL: desdeo_emo-1.4.2-py3-none-any.whl
  • Upload date:
  • Size: 100.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.1.8 CPython/3.7.7 Windows/10

File hashes

Hashes for desdeo_emo-1.4.2-py3-none-any.whl
Algorithm Hash digest
SHA256 72b058fd9c84ac942c6da5a1497075b1ba9c06f1bce2ee53bfcd92205e193906
MD5 68834b35b8e0c025eb324eccdeef71be
BLAKE2b-256 06b4c06eec334acff465fe19ca9b09104a1a6025a744ae7eb69b9e8daa1ed309

See more details on using hashes here.

Supported by

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