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GeneticSharp is a fast, extensible, multi-platform and multithreading C# Genetic Algorithm library that simplifies the development of applications using Genetic Algorithms (GAs).

Can be used in any kind of .NET Core and .NET Framework apps, like ASP .NET MVC, ASP .NET Core, Web Forms, UWP, Windows Forms, GTK#, Xamarin and Unity3D games.

Projects, papers, journals, books, tutorials, courses and apps using GeneticSharp

Features

Chromosomes

Fitness

Add your own fitness evaluation, implementing IFitness interface.

Populations

Generations

Operators strategy

Selections

Crossovers

Mutations

Reinsertions

Terminations

Randomizations

Task executors

Samples

Console samples

  • AutoConfig
  • Bitmap equality
  • Equality equation
  • Equation solver
  • Function builder
  • Ghostwriter
  • TSP (Travelling Salesman Problem)

GTK# samples

  • Bitmap equality
  • Function optimization
  • Sudoku
  • TSP (Travelling Salesman Problem)

Unity3D Samples

  • Car2D
  • TSP (Travelling Salesman Problem)
  • Wall Builder

Multi-platform

  • Mono, .NET Standard 2.0 and .NET Framework 4.6.2 support
  • Fully tested on Windows and MacOS

Code quality

Setup

.NET Standard 2.0 and .NET Framework 4.6.2

Only GeneticSharp:

install-package GeneticSharp

GeneticSharp and extensions (TSP, AutoConfig, Bitmap equality, Equality equation, Equation solver, Function builder, etc):

install-package GeneticSharp.Extensions

Unity3D

If want to use GeneticSharp on Unity3D you can use the latest GeneticSharp.unitypackage available on our release page.

Mono and .NET Framework 3.5

To install previous version that support .NET Framework 3.5:

install-package GeneticSharp -Version 1.2.0

Running samples

If you want to run the console, GTK# and Unity samples, just fork this repository and follow the instruction from our setup page wiki.

An easy way to run the Unity Samples, if you have a Android device, is download it from Google Play.

Usage

Creating your own fitness evaluation

public class MyProblemFitness : IFitness
{  
	public double Evaluate (IChromosome chromosome)
	{
		// Evaluate the fitness of chromosome.
	}
}

Creating your own chromosome

public class MyProblemChromosome : ChromosomeBase
{
	// Change the argument value passed to base construtor to change the length 
	// of your chromosome.
	public MyProblemChromosome() : base(10) 
	{
		CreateGenes();
	}

	public override Gene GenerateGene (int geneIndex)
	{
		// Generate a gene base on my problem chromosome representation.
	}

	public override IChromosome CreateNew ()
	{
		return new MyProblemChromosome();
	}
}

Running your GA

var selection = new EliteSelection();
var crossover = new OrderedCrossover();
var mutation = new ReverseSequenceMutation();
var fitness = new MyProblemFitness();
var chromosome = new MyProblemChromosome();
var population = new Population (50, 70, chromosome);

var ga = new GeneticAlgorithm(population, fitness, selection, crossover, mutation);
ga.Termination = new GenerationNumberTermination(100);

Console.WriteLine("GA running...");
ga.Start();

Console.WriteLine("Best solution found has {0} fitness.", ga.BestChromosome.Fitness);

FAQ

Having troubles?

How to improve it?

Create a fork of GeneticSharp.

Did you change it? Submit a pull request.

License

Licensed under the The MIT License (MIT). In others words, you can use this library for developement any kind of software: open source, commercial, proprietary, etc.

Thanks to

  • AppVeyor: open source license for continuous integration.
  • JetBrains: open source license for all products pack.
  • SMASHINGLOGO: GeneticSharp's logo.
  • SonarCloud: open source license for online inspection.