public override AbstractTrack Clone()
{
ClosedTrack track = new ClosedTrack(this.Genotype, _graph);
track.FirstParent = this.FirstParent;
track.SecondParent = this.SecondParent;
return (AbstractTrack)track;
}
public void ClosedTrackConstructorTest()
{
AbstractTrack track = new ClosedTrack(CountOfAllele, _graph, true);
Assert.IsTrue(track.Genotype.Length == CountOfAllele);
Assert.IsFalse(Array.Exists(track.Genotype, NegativeNumber));
Assert.IsFalse(Array.Exists(track.Genotype, UpperLimitNumber));
Assert.IsTrue(track.TypeOfCrossingover == AbstractCrossingover.WithoutCrossingover);
Assert.IsTrue(track.TypeOfMutation == AbstractMutation.WithoutMutation);
Assert.IsTrue(track.TypeOfSelection == AbstractSelection.WithoutSelection);
}
public void MyTestInitialize()
{
int[,] ribs = new int[15, 2] { { 0, 1 }, { 0, 2 }, { 0, 3 }, { 0, 4 }, { 0, 5 }, { 1, 2 }, { 1, 3 }, { 1, 4 }, { 1, 5 }, { 2, 3 }, { 2, 4 }, { 2, 5 }, { 3, 4 }, { 3, 5 }, { 4, 5 } };
double[] weights = new double[] { 1, 2, 3, 4, 1, 1, 3, 3, 3, 1, 2, 5, 1, 5, 1 };
_graph = new UndirectedConnectedGraph(ribs, weights);
_closedTracks = new AbstractTrack[4];
int[] trackPoints1 = new int[] { 0, 2, 1, 3, 5, 4 };
int[] trackPoints2 = new int[] { 1, 3, 0, 2, 4, 5 };
int[] trackPoints3 = new int[] { 2, 1, 0, 3, 5, 4 };
int[] trackPoints4 = new int[] { 2, 3, 0, 1, 4, 5 };
_closedTracks[0] = new ClosedTrack(trackPoints1, _graph);
_closedTracks[1] = new ClosedTrack(trackPoints2, _graph);
_closedTracks[2] = new ClosedTrack(trackPoints3, _graph);
_closedTracks[3] = new ClosedTrack(trackPoints4, _graph);
}
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);
}
}
public override AbstractTrack EmptyClone()
{
ClosedTrack track = new ClosedTrack(this.Genotype.Length, _graph, false);
return (AbstractTrack)track;
}
public void MyTestInitialize()
{
int[,] ribs = new int[6, 2] { { 0, 1 }, { 0, 2 }, { 0, 3 }, { 1, 2 }, { 1, 3 }, { 2, 3 } };
double[] weights = new double[] { 3, 5.5, 10, 7, 8, 9 };
_graph = new UndirectedConnectedGraph(ribs, weights);
_track = new ClosedTrack(_trackPoints, _graph);
}
