public void MutationTest()
{
NotRandomMutation target = new NotRandomMutation();
target.Mutation(_mutant);
Assert.IsFalse(TwoIntArrayEquals(_mutant.Genotype, _subject.Genotype));
Assert.IsTrue(IsItemsUnique(_mutant.Genotype));
Assert.IsTrue(_mutant.TypeOfMutation == NotRandomMutation.MutationName);
}
public Configuration()
{
AliasCrossingover = new List<string>();
AliasMutations = new List<string>();
AliasSelection = new List<string>();
ConfigName = "Новая конфигурация";
AlgMode = AlgorithmMode.Singl;
CountOfReplays = 1;
ProbOfCrossingover = 100;
ProbOfMutation = 100;
FitnessParam = 10;
Mutation = new NotRandomMutation();
AliasMutations.Add(Mutation.GetName());
Crossingover = new CyclicalCrossingover();
AliasCrossingover.Add(Crossingover.GetName());
Selection = new TournamentSelection();
AliasSelection.Add(Selection.GetName());
Graph = new UndirectedConnectedGraph(10);
FitnessFunction = new BestReps((int)FitnessParam);
Tracks = new AbstractTrack[10];
Random r = new Random();
for (int i = 0; i < Tracks.Length; i++)
{
int[] points = new int[10];
for (int j = 0; j < points.Length; j++)
{
points[j] = -1;
}
int newRandomChromosome = r.Next(points.Length - 1);
for (int j = 0; j < points.Length; j++)
{
while (points.Contains(newRandomChromosome))
{
newRandomChromosome = r.Next(points.Length);
}
points[j] = newRandomChromosome;
}
Tracks[i] = new ClosedTrack(points, Graph);
}
}
