Skip to main content

Framework for Evolutionary Algorithms in Torch

Project description

FFEAT

Framework For Evolutionary Algorithms in Torch


This library implements various evolutionary algorithms, specifically

  • Genetic Algorithms in ffeat.genetic module.
  • Real-Coded Evolutionary Algorithms in ffeat.strategies module.
  • Evolution Strategies in ffeat.strategies module.
  • Particle Swarm Optimisation in ffeat.pso module.

The algorithms are fully vectorized and can run on GPU.

Each module consists of selection, crossover, and mutation submodule implementing relevant operators (with the exception of PSO algorithm). The operators may be arbitrarily combined.

See examples for more information on how to use the library.

This library was developed as part of my master thesis: https://github.com/PatrikValkovic/MasterThesis. You can find more information about the implementation there.


Author: Patrik Valkovič

License: MIT

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

FFEAT-1.0.0.tar.gz (47.3 kB view hashes)

Uploaded Source

Built Distribution

FFEAT-1.0.0-py3-none-any.whl (77.0 kB view hashes)

Uploaded Python 3

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