public void TestBooleanArrayWithOnePoint()
{
var p = new Population(new BooleanChromosome(), 10, 20);
var ga = new GeneticAlgorithm(p, new EliteSelection(), new BooleanChromosomeCrossover(), new ElitistReinsertion());
var t = new bool[BooleanChromosome.Length];
for (var i = 0; i < t.Length; i++)
{
t[i] = i % 2 == 0;
}
for (var j = 0; j < p.Size; j++)
{
((BooleanChromosome)p[j]).Evaluate(t);
}
for (var i = 0; i < 1000; i++)
{
ga.BeginGeneration();
for (var j = 0; j < p.Size; j++)
{
((BooleanChromosome)p[j]).Evaluate(t);
}
ga.EndGeneration();
}
var result = (BooleanChromosome)ga.FittestChromosome;
CollectionAssert.AreEqual(t, result.Value);
}
public void TestTargetNumber()
{
var p = new Population(new TargetNumberChromosome(), 6, 12);
var ga = new GeneticAlgorithm(p, new EliteSelection(), new TargetNumberCrossover(), new ElitistReinsertion());
for (var j = 0; j < p.Size; j++)
{
((TargetNumberChromosome)p[j]).Evaluate();
}
for (var i = 0; i < 500; i++)
{
ga.BeginGeneration();
for (var j = 0; j < p.Size; j++)
{
((TargetNumberChromosome)p[j]).Evaluate();
}
ga.EndGeneration();
}
var result = (TargetNumberChromosome)ga.FittestChromosome;
Assert.IsTrue(Math.Abs(result.Value - 42.0) < 0.01);
}