A playground for evolutionary computation in Julia

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.


  • Random population generators (vectors and particles)
  • Parent selection operators
  • Several crossover and mutation methods
  • Test functions for benchmarking
  • Convenient result reporting and a statistics logbook

You can combine these blocks to make your own algorithms or use some of the included minimisers: a generational GA, 1+1 Evolutionary Algorithm and Particle Swarm Optimisation solver.


You can install EvoLP from the REPL using the built-in package manager:

julia> import Pkg
julia> Pkg.add("EvoLP")

Getting started

  • Read the documentation.
  • See the code in GitHub.
  • Browse some of the examples to see how to use the built-in algorithms.
  • For a more comprehensive tutorial, read the 8-queen problem where we make an algorithm from scratch.


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.

Xavier F. C. Sánchez Díaz
Xavier F. C. Sánchez Díaz
PhD candidate in Artificial Intelligence

PhD candidate in Artificial Intelligence at the Department of Computer Science (IDI) of the Norwegian University of Science and Technology