GiveAGap 1.0.2

There is a newer version of this package available.
See the version list below for details.

dotnet add package GiveAGap --version 1.0.2

NuGet\Install-Package GiveAGap -Version 1.0.2

This command is intended to be used within the Package Manager Console in Visual Studio, as it uses the NuGet module's version of Install-Package.

<PackageReference Include="GiveAGap" Version="1.0.2" />

For projects that support PackageReference, copy this XML node into the project file to reference the package.

paket add GiveAGap --version 1.0.2

The NuGet Team does not provide support for this client. Please contact its maintainers for support.

#r "nuget: GiveAGap, 1.0.2"

#r directive can be used in F# Interactive and Polyglot Notebooks. Copy this into the interactive tool or source code of the script to reference the package.

// Install GiveAGap as a Cake Addin
#addin nuget:?package=GiveAGap&version=1.0.2

// Install GiveAGap as a Cake Tool
#tool nuget:?package=GiveAGap&version=1.0.2

The NuGet Team does not provide support for this client. Please contact its maintainers for support.

Headings

Install the package and then add at least this line of code below to run once the algorithm

Code Block

var mutationProb = 0.1f; var crossOverProb = 0.8f; var dimVincoli = 1000; var dimVars = 15; var trPerc = 0.5; var vdPerc = 0.25; var myTest = new SynthTest(dimVincoli, dimVars, trPerc, vdPerc, 1, 1); // or Create another test expanding SynthTest.cs GeneticAlgorithmSETUP setup = new GeneticAlgorithmSETUP(myTest, dimVincoli, dimVars, trPerc, vdPerc, 1, crossOverProb, mutationProb); setup.minFit = 0.45; setup.forcedINOUT = Vector<double>.Build.Dense(setup.dimVars); // modify your ForcedInOutClass var forcedINOUT = setup.forcedINOUT; var result = setup.Start(0.8,30,true); // Termination Conditions (minFit,minGen,and) Console.WriteLine("SELECTED: " + result.Item1); Console.WriteLine("In " + result.Item2 + " generations"); Console.WriteLine("In " + result.Item3 + " seconds"); Console.WriteLine("Fitness on TS " + result.Item4); Console.WriteLine("Fitness on TR VD " + result.Item5); Console.WriteLine("*****************");

Explaination

Basically you need to choose mutation and crossover probability, then setup the algorithm giving him the size of the input Matrix, and then calling setup.Start() the algorithm starts and when execution finishes you get a tuple with all element you need for the analysis

Product	Compatible and additional computed target framework versions.
.NET Framework	net45 is compatible. net451 was computed. net452 was computed. net46 was computed. net461 was computed. net462 was computed. net463 was computed. net47 was computed. net471 was computed. net472 was computed. net48 was computed. net481 was computed.

Compatible target framework(s)

Included target framework(s) (in package)

Learn more about Target Frameworks and .NET Standard.

This package has no dependencies.

NuGet packages

This package is not used by any NuGet packages.

GitHub repositories

This package is not used by any popular GitHub repositories.

Version	Downloads	Last updated
1.0.3	1,587	11/11/2017
1.0.2	1,594	11/5/2017
1.0.1	1,503	11/5/2017
1.0.0	1,604	11/5/2017