public ParallelGA(int GeneSize, int GenerationSize, int GenerationCarryover, int NumThreads, FittnessDelegate fittness)
{
this.generationSize = GenerationSize;
this._fittness = fittness;
this.generationCarryover = GenerationCarryover;
this._numThreads = NumThreads;
this.CompletedTesting = new List <chromosome>();
this.NextGeneration = new List <chromosome>();
//genrate rangom 0th generation
Random rand = new Random();
for (int i = 0; i < generationSize; i++)
{
chromosome c = new chromosome();
c.gene = Enumerable.Range(0, GeneSize)
.Select(j => new Tuple <int, int>(rand.Next(GeneSize), j))
.OrderBy(k => k.Item1)
.Select(l => l.Item2).ToList();
this.CurrentGeneration.Add(c);
}
this.generation = 0;
this.HighScore = Int64.MaxValue;
this.HighScoreGeneration = -1;
}
public StandardGA(int GeneSize, int GenerationSize, int GenerationCarryover, FittnessDelegate fittness)
{
this.generationSize = GenerationSize;
this.generationCarryover = GenerationCarryover;
this._fittness = fittness;
//create random generation 0
Random rand = new Random();
for (int i = 0; i < generationSize; i++)
{
chromosome c = new chromosome();
c.gene = Enumerable.Range(0, GeneSize)
.Select(j => new Tuple <int, int>(rand.Next(GeneSize), j))
.OrderBy(k => k.Item1)
.Select(l => l.Item2).ToList();
this.CurrentGeneration.Add(c);
}
this.generation = 0;
this.HighScore = Int64.MaxValue;
this.HighScoreGeneration = -1;
}
