GeneticSharpCore 1.0.1

GeneticSharp is a library that handles the mechanism of a generic algorithm implementation. It automatically creates the population, the reproduction and mutation phases.

Install-Package GeneticSharpCore -Version 1.0.1
dotnet add package GeneticSharpCore --version 1.0.1
<PackageReference Include="GeneticSharpCore" Version="1.0.1" />
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add GeneticSharpCore --version 1.0.1
The NuGet Team does not provide support for this client. Please contact its maintainers for support.
#r "nuget: GeneticSharpCore, 1.0.1"
#r directive can be used in F# Interactive, C# scripting and .NET Interactive. Copy this into the interactive tool or source code of the script to reference the package.
// Install GeneticSharpCore as a Cake Addin
#addin nuget:?package=GeneticSharpCore&version=1.0.1

// Install GeneticSharpCore as a Cake Tool
#tool nuget:?package=GeneticSharpCore&version=1.0.1
The NuGet Team does not provide support for this client. Please contact its maintainers for support.

GeneticSharp

GeneticSharp is a .Net Core library that that handles the mecanics of a generic algorithm implementation. It automatically creates the population, do by itself the reproduction and mutation phases according with the strategy and configuration set.

GeneticSharp do the hard job for you and let you focus on the most important piece, the problem you are solving. You can direct focus on designing your model, chromosses, and the fitness method.

GeneticSharp accepts as a model any C# POCO class. It needs to be a class, needs to implement the IEvolutionaryIndividual interface and to have the default constructor.

Simplest Usage

using GeneticSharp;
// ...
var geneticEvolution = new GeneticEvolution<MyModel>();

// gen1
var gen1Result = geneticEvolution.Evolve();
Console.WriteLine(gen1Result.BestIndividual);

// gen2
var gen2Result = geneticEvolution.Evolve();
Console.WriteLine(gen2Result.BestIndividual);

Configuration

Supported variables

  1. Population Size: amount of individuals (population) per generation
  2. Natural Selection Rate: population percetage that is selected to reproduce and generate new individuals to the next gen
  3. Mutation Rate
  4. Collection Types Sizes

Types supporteds

  1. string
  2. int, short, long
  3. float, double, decimal
  4. Nullable
  5. bool
  6. DateTime
  7. IEnumerable<T>, IList<T>, List<T>, Array
  8. Enums

GeneticSharp

GeneticSharp is a .Net Core library that that handles the mecanics of a generic algorithm implementation. It automatically creates the population, do by itself the reproduction and mutation phases according with the strategy and configuration set.

GeneticSharp do the hard job for you and let you focus on the most important piece, the problem you are solving. You can direct focus on designing your model, chromosses, and the fitness method.

GeneticSharp accepts as a model any C# POCO class. It needs to be a class, needs to implement the IEvolutionaryIndividual interface and to have the default constructor.

Simplest Usage

using GeneticSharp;
// ...
var geneticEvolution = new GeneticEvolution<MyModel>();

// gen1
var gen1Result = geneticEvolution.Evolve();
Console.WriteLine(gen1Result.BestIndividual);

// gen2
var gen2Result = geneticEvolution.Evolve();
Console.WriteLine(gen2Result.BestIndividual);

Configuration

Supported variables

  1. Population Size: amount of individuals (population) per generation
  2. Natural Selection Rate: population percetage that is selected to reproduce and generate new individuals to the next gen
  3. Mutation Rate
  4. Collection Types Sizes

Types supporteds

  1. string
  2. int, short, long
  3. float, double, decimal
  4. Nullable
  5. bool
  6. DateTime
  7. IEnumerable<T>, IList<T>, List<T>, Array
  8. Enums

NuGet packages

This package is not used by any NuGet packages.

GitHub repositories

This package is not used by any popular GitHub repositories.

Version History

Version Downloads Last updated
1.0.1 439 2/5/2019
1.0.0 378 11/14/2018