.NET遗传算法框架_C#_代码_下载

[](https://travis-ci.org/afonsof/EvolveSharp) [](http://gruntjs.com/) A Genetic Algorithm Framework for .NET <a href="http://afonsof.github.io/EvolveSharp" target="_blank">Visit our website</a> ## Getting Started #### 1. Setting Up Create a Console Application and install EvoleSharp using Nuget: ``` PM> Install-Package EvolveSharp ``` #### 2. Create a fitness function In this simple example we are creating a fitness function to sum all genes of an individual ```c# public class ExampleFitnessFunction : IFitnessFunction<double> { public double Evaluate(IIndividual<double> individual) { var sum = 0.0; for (var i = 0; i < individual.Length; i++) { sum += individual[i]; } return sum; } } ``` #### 3. Instantiate the GeneticAlgorithm class and call the Evolve method You can set 3 parameters: 1. Population count: How many individuals each population will have 2. Gene count: How many genes each individual will have 3. Generation count: How many generations will occour ```c# class Program { static void Main(string[] args) { const int populationCount = 100; const int generationCount = 10000; const int geneCount = 10; var ga = new GeneticAlgorithm(populationCount, geneCount, new ExampleFitnessFunction()); ga.Evolve(generationCount); } } ``` #### Other information 1. You can create your own mutation, selection, crossover and initializer class. You just need to inherit the respective interface. 2. You can set the ```Mutator```, ```CrossoverMethod```, ```Selector``` and ```Initializer``` after instantiate the ```GeneticAlgorithm``` class. 3. You can create and set your own reporter in ```GeneticAlgorithm``` class. ## Sample Clone EvolveSharp and try the Travelling salesman problem sample <img src="http://afonsof.github.io/EvolveSharp/images/tsp.png" /> ## Contributing Please use the issue tracker and pull requests. ## License Copyright (c) 2014 Afonso França Licensed under the MIT license. [](https://bitdeli.com/free "Bitdeli Badge")