Merge branch 'release/v2.4.0'

Author: giacomelli

README.md

@@ -47,10 +47,21 @@ Can be used in any kind of .NET Core and .NET Framework apps, like ASP .NET MVC,
 Add your own fitness evaluation, implementing [IFitness](src/GeneticSharp.Domain/Fitnesses/IFitness.cs) interface.
 
 ### [Populations](src/GeneticSharp.Domain/Populations)
+   - [Population](src/GeneticSharp.Domain/Populations/Population.cs)
+   - [TplPopulation](src/GeneticSharp.Domain/Populations/TplPopulation.cs)
+   - Others populations can be added implementing [IPopulation](src/GeneticSharp.Domain/IPopulation) interface or extending [Population](src/GeneticSharp.Domain/Populations/Population.cs).
+
+### [Generations](src/GeneticSharp.Domain/Populations/Generation.cs)
    - [Generation](src/GeneticSharp.Domain/Populations/Generation.cs)
    - [Generation strategy](src/GeneticSharp.Domain/Populations/IGenerationStrategy.cs)
      - [Performance strategy](src/GeneticSharp.Domain/Populations/PerformanceGenerationStrategy.cs)
      - [Tracking strategy](src/GeneticSharp.Domain/Populations/TrackingGenerationStrategy.cs)  
+     - Others generation strategies can be added implementing [IGenerationStrategy.cs](src/GeneticSharp.Domain/IGenerationStrategy.cs) interface.
+     
+### [Operators strategy](src/GeneticSharp.Domain/src/GeneticSharp.Domain/IOperatorsStrategy.cs)
+   - [DefaultOperatorsStrategy](src/GeneticSharp.Domain/DefaultOperatorsStrategy.cs)
+   - [TplOperatorsStrategy](src/GeneticSharp.Domain/TplOperatorsStrategy.cs)
+   - Others operators strategies can be added implementing [IOperatorsStrategy](src/GeneticSharp.Domain/IOperatorsStrategy.cs) interface.
 
 ### [Selections](src/GeneticSharp.Domain/Selections)
    - [Elite](src/GeneticSharp.Domain/Selections/EliteSelection.cs) (also know as Truncate or Truncation)
@@ -60,6 +71,7 @@ Add your own fitness evaluation, implementing [IFitness](src/GeneticSharp.Domain
    - Others selections can be added implementing [ISelection](src/GeneticSharp.Domain/Selections/ISelection.cs) interface or extending [SelectionBase](src/GeneticSharp.Domain/Selections/SelectionBase.cs). 
 
 ### [Crossovers](src/GeneticSharp.Domain/Crossovers)
+   - [Alternating-position (AP)](src/GeneticSharp.Domain/Crossovers/AlternatingPositionCrossover.cs)  
    - [Cut and Splice](src/GeneticSharp.Domain/Crossovers/CutAndSpliceCrossover.cs) 
    - [Cycle (CX)](src/GeneticSharp.Domain/Crossovers/CycleCrossover.cs)   
    - [One-Point (C1)](src/GeneticSharp.Domain/Crossovers/OnePointCrossover.cs)
@@ -70,6 +82,7 @@ Add your own fitness evaluation, implementing [IFitness](src/GeneticSharp.Domain
    - [Three parent](src/GeneticSharp.Domain/Crossovers/ThreeParentCrossover.cs)
    - [Two-Point (C2)](src/GeneticSharp.Domain/Crossovers/TwoPointCrossover.cs)
    - [Uniform](src/GeneticSharp.Domain/Crossovers/UniformCrossover.cs)
+   - [Voting Recombination (VR)](src/GeneticSharp.Domain/Crossovers/VotingRecombinationCrossover.cs)  
    - Others crossovers can be added implementing [ICrossover](src/GeneticSharp.Domain/Crossovers/ICrossover.cs) interface or extending [CrossoverBase](src/GeneticSharp.Domain/Crossovers/CrossoverBase.cs).   
 
 ### [Mutations](src/GeneticSharp.Domain/Mutations)
@@ -102,28 +115,38 @@ Add your own fitness evaluation, implementing [IFitness](src/GeneticSharp.Domain
    - [Fast random](src/GeneticSharp.Domain/Randomizations/FastRandomRandomization.cs)   
    - If you need a special kind of randomization for your GA, just implement the [IRandomization](src/GeneticSharp.Domain/Randomizations/IRandomization.cs) interface.
 
+### [Task executors](src/GeneticSharp.Infrastructure.Framework/Threading/ITaskExecutor.cs)
+   - [LinearTaskExecutor](src/GeneticSharp.Infrastructure.Framework/Threading/LinearTaskExecutor.cs)
+   - [ParallelTaskExecutor](src/GeneticSharp.Infrastructure.Framework/Threading/ParallelTaskExecutor.cs)
+   - [TplTaskExecutor](src/GeneticSharp.Infrastructure.Framework/Threading/TplTaskExecutor.cs)
+   - Others task executors can be added implementing [ITaskExecutor](src/GeneticSharp.Infrastructure.Framework/Threading/ITaskExecutor.cs) interface.
+   
 ##  Samples
-### [Console sample](src/GeneticSharp.Runner.ConsoleApp)
+### [Console samples](src/GeneticSharp.Runner.ConsoleApp)
 - AutoConfig
 - Bitmap equality
 - Equality equation
 - Equation solver
 - Function builder
+- Ghostwriter
+- TSP (Travelling Salesman Problem)
 
 ![](docs/gifs/GeneticSharp-ConsoleApp-EquationSolver-FunctionBuilder.gif)
 
-- Ghostwriter
-- TSP (Travelling Salesman Problem)
 
-### [GTK# sample](src/GeneticSharp.Runner.GtkApp)
+### [GTK# samples](src/GeneticSharp.Runner.GtkApp)
+- Bitmap equality
+- Function optimization
+- Sudoku
+- TSP (Travelling Salesman Problem)
 
-#### TSP (Travelling Salesman Problem), Function optimization and Sudoku
 ![](docs/gifs/GeneticSharp-GtkApp.gif)
 
-#### Bitmap equality
-![](docs/gifs/GeneticSharp-BitmapEquality_sample01.gif)
-
 ### [Unity3D Samples](src/GeneticSharp.Runner.UnityApp)
+- Car2D
+- TSP (Travelling Salesman Problem)
+- Wall Builder
+
 [![](docs/screenshots/GeneticSharp-UnityApp.png)](https://youtu.be/xXqNcgeOU_g)
 [![](docs/images/google-play-badge.png)](https://play.google.com/store/apps/details?id=br.com.diegogiacomelli.geneticsharprunnersunityapp)
 
@@ -132,14 +155,10 @@ Add your own fitness evaluation, implementing [IFitness](src/GeneticSharp.Domain
 - Mono, .NET Standard 2.0 and .NET Framework 4.6.2 support.
 - Fully tested on Windows and MacOS.
 
-![](docs/screenshots/VisualStudioMacAndWin.png)
-
 ## Code quality
 - 100% unit test code coverage.
-- FxCop validated.
-- Code duplicated verification.
-- Good (and well used) design patterns.  
 - 100% code documentation
+- [SonarCloud](https://sonarcloud.io/dashboard?id=GeneticSharp) validated.
 
 --------
 
@@ -170,6 +189,8 @@ 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](https://github.com/giacomelli/GeneticSharp/wiki/setup) page wiki.
 
+An easy way to run the Unity Samples, if you have a Android device, is download it from [Google Play](https://play.google.com/store/apps/details?id=br.com.diegogiacomelli.geneticsharprunnersunityapp).
+
 ## Usage
 
 ### Creating your own fitness evaluation 
@@ -228,33 +249,6 @@ ga.Start();
 
 Console.WriteLine("Best solution found has {0} fitness.", ga.BestChromosome.Fitness);
 ```
-
---------
-
-## Roadmap
- - Add new problems/classic sample
-   - Checkers 
-   - Time series   
-   - Knapsack problem
- - Add new selections   
-  - Reward-based
- - Add new crossovers   
-   - Voting recombination
-   - Alternating-position (AP)
-   - Sequential Constructive (SCX)    
-   - Shuffle crossover
-   - Precedence Preservative Crossover (PPX)
- - Add new mutations
-   - Non-Uniform
-   - Boundary
-   - Gaussian 
- - Add new terminations
-   - Fitness convergence 
-   - Population convergence
-   - Chromosome convergence   
- - New samples
-   - Xamarin runner app (sample)
- - Parallel populations (islands) 
 
 --------
 
@@ -266,10 +260,10 @@ Having troubles?
 - Tutorials
    - [Function optimization with GeneticSharp](http://diegogiacomelli.com.br/function-optimization-with-geneticsharp/) 
    - [TSP with GeneticSharp and Unity3D](http://diegogiacomelli.com.br/tsp-with-GeneticSharp-and-Unity3d/)
-- Ask on Twitter [@ogiacomelli](http://twitter.com/ogiacomelli).
 - Ask on [Stack Overflow](http://stackoverflow.com/questions/tagged/geneticsharp) using the tag [GeneticSharp](http://stackoverflow.com/questions/tagged/geneticsharp).
- 
- --------
+- Open an [issue](https://github.com/giacomelli/GeneticSharp/issues).
+
+--------
 
 ## How to improve it?
 
@@ -278,8 +272,8 @@ Create a fork of [GeneticSharp](https://github.com/giacomelli/GeneticSharp/fork)
 Did you change it? [Submit a pull request](https://github.com/giacomelli/GeneticSharp/pull/new/master).
 
 ## 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 and alien.
+Licensed under the The [MIT License (MIT)](LICENSE).
+In others words, you can use this library for developement any kind of software: open source, commercial, proprietary, etc.
 
 # Thanks to
 I would like to thanks to the guys from [SMASHINGLOGO (https://smashinglogo.com)](https://smashinglogo.com/) for the amazing GeneticSharp logo.

appveyor.yml

@@ -1,4 +1,4 @@
-version: 2.2.{build}
+version: 2.4.{build}
 os: Visual Studio 2017
 configuration: Release
 environment:
@@ -15,11 +15,7 @@ assembly_info:
   assembly_informational_version: '{version}'
 
 install:
-- cmd: choco install gtksharp    
-
-nuget:
-  account_feed: true
-  project_feed: true
+- cmd: choco install gtksharp
 
 before_build:
 - cmd: dotnet --version
@@ -47,9 +43,9 @@ after_build:
 - cmd: >-   
     mkdir .\src\nuget
 
-    dotnet pack src/GeneticSharp.Domain/GeneticSharp.Domain.csproj -c release --no-build --output ../nuget /p:PackageVersion=2.2.0
+    dotnet pack src/GeneticSharp.Domain/GeneticSharp.Domain.csproj -c release --no-build --output ../nuget /p:PackageVersion=2.4.0
     
-    dotnet pack src/GeneticSharp.Extensions/GeneticSharp.Extensions.csproj -c release --no-build --output ../nuget /p:PackageVersion=2.2.0
+    dotnet pack src/GeneticSharp.Extensions/GeneticSharp.Extensions.csproj -c release --no-build --output ../nuget /p:PackageVersion=2.4.0
 
 test_script:
 - cmd: dotnet clean src/GeneticSharp.Domain.UnitTests

docs/Crossover operators in genetic algorithms - A review.pdf

@@ -0,0 +1,153 @@
+using System.Collections.Generic;
+using GeneticSharp.Domain.Chromosomes;
+using GeneticSharp.Domain.Crossovers;
+using GeneticSharp.Domain.Randomizations;
+using NUnit.Framework;
+using NSubstitute;
+using System;
+using GeneticSharp.Domain.Populations;
+using GeneticSharp.Domain.Fitnesses;
+using System.Linq;
+using GeneticSharp.Domain.Selections;
+using GeneticSharp.Domain.Mutations;
+using GeneticSharp.Domain.Terminations;
+using System.Diagnostics;
+using GeneticSharp.Extensions.Tsp;
+
+namespace GeneticSharp.Domain.UnitTests.Crossovers
+{
+    [TestFixture]
+    [Category("Crossovers")]
+    public class AlternatingPositionCrossoverTest
+    {
+        [TearDown]
+        public void Cleanup()
+        {
+            RandomizationProvider.Current = new BasicRandomization();
+        }
+
+        [Test]
+        public void Cross_ParentWithNoOrderedGenes_Exception()
+        {
+            var target = new AlternatingPositionCrossover();
+
+            var chromosome1 = Substitute.For<ChromosomeBase>(8);
+            chromosome1.ReplaceGenes(0, new Gene[] {
+                new Gene(8),
+                new Gene(2),
+                new Gene(3),
+                new Gene(4),
+                new Gene(6),
+                new Gene(5),
+                new Gene(7),
+                new Gene(1)
+            });
+
+            // 3 7 5 1 6 8 2 4
+            var chromosome2 = Substitute.For<ChromosomeBase>(8);
+            chromosome2.ReplaceGenes(0, new Gene[] {
+                new Gene(1),
+                new Gene(2),
+                new Gene(3),
+                new Gene(4),
+                new Gene(5),
+                new Gene(5),
+                new Gene(6),
+                new Gene(7)
+            });
+
+            Assert.Catch<CrossoverException>(() =>
+            {
+                target.Cross(new List<IChromosome>() { chromosome1, chromosome2 });
+            }, "The Alternating-position (AP) can be only used with ordered chromosomes. The specified chromosome has repeated genes.");
+        }
+
+        [Test]
+        public void Cross_DocumentationSample_Child()
+        {
+            var target = new AlternatingPositionCrossover();
+
+            // 1 2 3 4 5 6 7 8
+            var chromosome1 = Substitute.For<ChromosomeBase>(8);
+            chromosome1.ReplaceGenes(0, new Gene[] {
+                new Gene(1),
+                new Gene(2),
+                new Gene(3),
+                new Gene(4),
+                new Gene(5),
+                new Gene(6),
+                new Gene(7),
+                new Gene(8)
+            });
+
+            var child1 = Substitute.For<ChromosomeBase>(8);
+            chromosome1.CreateNew().Returns(child1);
+
+            // 3 7 5 1 6 8 2 4
+            var chromosome2 = Substitute.For<ChromosomeBase>(8);
+            chromosome2.ReplaceGenes(0, new Gene[] {
+                new Gene(3),
+                new Gene(7),
+                new Gene(5),
+                new Gene(1),
+                new Gene(6),
+                new Gene(8),
+                new Gene(2),
+                new Gene(4)
+            });
+            var child2 = Substitute.For<ChromosomeBase>(8);
+            chromosome2.CreateNew().Returns(child2);
+
+            var actual = target.Cross(new List<IChromosome>() { chromosome1, chromosome2 });
+
+            Assert.AreEqual(2, actual.Count);
+
+            // 1 3 2 7 5 4 6 8
+            var actualChild = actual[0];
+            Assert.AreEqual(8, actualChild.Length);
+           
+            Assert.AreEqual(1, actualChild.GetGene(0).Value);
+            Assert.AreEqual(3, actualChild.GetGene(1).Value);
+            Assert.AreEqual(2, actualChild.GetGene(2).Value);
+            Assert.AreEqual(7, actualChild.GetGene(3).Value);
+            Assert.AreEqual(5, actualChild.GetGene(4).Value);
+            Assert.AreEqual(4, actualChild.GetGene(5).Value);
+            Assert.AreEqual(6, actualChild.GetGene(6).Value);
+            Assert.AreEqual(8, actualChild.GetGene(7).Value);
+
+            // 3 1 7 2 5 4 6 8
+            actualChild = actual[1];
+            Assert.AreEqual(8, actualChild.Length);
+            Assert.AreEqual(3, actualChild.GetGene(0).Value);
+            Assert.AreEqual(1, actualChild.GetGene(1).Value);
+            Assert.AreEqual(7, actualChild.GetGene(2).Value);
+            Assert.AreEqual(2, actualChild.GetGene(3).Value);
+            Assert.AreEqual(5, actualChild.GetGene(4).Value);
+            Assert.AreEqual(4, actualChild.GetGene(5).Value);
+            Assert.AreEqual(6, actualChild.GetGene(6).Value);
+            Assert.AreEqual(8, actualChild.GetGene(7).Value);
+        }
+
+        [Test]
+        public void GA_WithAlternatingPositionCrossover_Evolve()
+        {
+            var chromosome = new TspChromosome(50);
+            var population = new Population(50, 50, chromosome)
+            {
+                GenerationStrategy = new TrackingGenerationStrategy()
+            };
+            var fitness = new TspFitness(chromosome.Length, 0, 1000, 0, 1000);
+            var crossover = new AlternatingPositionCrossover();
+            var ga = new GeneticAlgorithm(population, fitness, new EliteSelection(), crossover, new ReverseSequenceMutation())
+            {
+                Termination = new GenerationNumberTermination(100)
+            };
+
+            ga.Start();
+          
+            Assert.Less(
+                population.Generations.First().BestChromosome.Fitness.Value,
+                population.Generations.Last().BestChromosome.Fitness.Value);
+        }
+    }
+}