EvoLP - An evolutionary computation playground

Welcome to the documentation for EvoLP!

GitHub source Julia version Code Style: Blue ColPrac: Contributor's Guide on Collaborative Practices for Community Packages

What is EvoLP?

EvoLP is a playground for evolutionary computation in Julia. It provides a set of predefined building blocks that can be coupled together to quickly generate evolutionary computation solvers and compute statistics for a variety of optimisation tasks, including discrete, continuous and combinatorial optimisation.


Combine these blocks to make your own algorithms or use some of the included minimisers: GA, 1+1EA and PSO. Additionally, you can extend EvoLP to create new operators.

Getting started

  • Read the quick start page for information about installation and to get a quick overview.
  • Browse some of the examples to see how to use the built-in algorithms.
  • For a more comprehensive tutorial, read the 8-queens problem where we make an algorithm from scratch.

Alternatively, you can browse the type and functions indices to view all available functionality.

Citing EvoLP.jl

If you find EvoLP.jl useful in your work or research, we kindly request that you cite the following paper:

  address = {Bergen, NO},
  author = {Sánchez-Díaz, Xavier F. C. and Mengshoel, Ole Jakob},
  booktitle = {Proceedings of the 5th Symposium of the Norwegian AI Society},
  editor = {Galimullin, Rustam and Touileb, Samia},
  month = jun,
  publisher = {CEUR Workshop Proceedings},
  series = {NAIS 2023: Symposium of the Norwegian AI Society 2023},
  title = {{EvoLP.jl: A Playground for Evolutionary Computation in Julia}},
  url = {https://ceur-ws.org/Vol-3431/},
  year = {2023}


EvoLP started as a toolbox for internal use by PhD students of NTNU's Open AI Lab, and whose funding is provided by Project no. 311284 by The Research Council of Norway.


EvoLP is licensed under the MIT License which makes it free and open source.