public void Crossover(ref ScheduleGenome p2, ref ScheduleGenome o1)
{
int cutpoint = SimpleRNG.Next(0, _jobsLength);
//Debug.Write(Environment.NewLine + "Distance between " + p1 + " - " + p2 + ": " + population[p1].Distance(population[p2]));
for (int i = 0; i < _jobsLength; i++)
{
o1.JobGenes[i] = JobGenes[i];
}
Debug.Assert(o1.IsValid(), "Invalid creature before crossover");
List <int> remainder = new List <int>(p2.JobGenes);
for (int i = 0; i < cutpoint; i++)
{
remainder.Remove(JobGenes[i]);
}
for (int i = cutpoint; i < _jobsLength; i++)
{
o1.JobGenes[i] = remainder[i - cutpoint];
}
Debug.Assert(o1.IsValid(), "Invalid creature after crossover");
RealCrossover(ref p2, ref o1);
CombinationCrossover(ref p2, ref o1);
}
public void RealCrossover(ref ScheduleGenome p2, ref ScheduleGenome o1)
{
switch (realCrossover)
{
case RealCrossoverOp.MeanWithNoise:
// Mean-with-noise Crossover:
for (int i = 0; i < _modesLength; i++)
{
double mean = TimeGenes[i] + p2.TimeGenes[i];
mean = mean / 2.0;
o1.TimeGenes[i] = SimpleRNG.GetNormal(mean, 0.5);
if (o1.TimeGenes[i] < 0.0)
{
o1.TimeGenes[i] = 0.0;
}
}
break;
case RealCrossoverOp.Uniform:
// Uniform Crossover:
int cutpoint = SimpleRNG.Next(0, _modesLength + 1);
for (int i = 0; i < cutpoint; i++)
{
o1.TimeGenes[i] = TimeGenes[i];
}
for (int i = cutpoint; i < _modesLength; i++)
{
o1.TimeGenes[i] = p2.TimeGenes[i];
}
break;
}
}
public ScheduleGenome(ScheduleGenome g)
{
JobGenes = new int[g._jobsLength];
TimeGenes = new double[g._timesLength];
ModeGenes = new int[g._modesLength];
_delayRate = g._delayRate;
_delayMean = g._delayMean;
_jobsLength = g._jobsLength;
_timesLength = g._timesLength;
_modesLength = g._modesLength;
_numberOfModes = g._numberOfModes;
_mutationRate = g._mutationRate;
realCrossover = g.realCrossover;
for (int i = 0; i < g._jobsLength; i++)
{
JobGenes[i] = g.JobGenes[i];
}
for (int i = 0; i < g._timesLength; i++)
{
TimeGenes[i] = g.TimeGenes[i];
}
for (int i = 0; i < g._modesLength; i++)
{
ModeGenes[i] = g.ModeGenes[i];
}
fitness = -1;
}
public double Distance(ScheduleGenome c)
{
double d = 0;
for (int i = 0; i < _modesLength; i++)
{
d += Math.Pow(TimeGenes[i] - c.TimeGenes[i], 2.0);
}
return(Math.Sqrt(d));
}
public void CombinationCrossover(ref ScheduleGenome p2, ref ScheduleGenome o1)
{
int cutpoint = SimpleRNG.Next(0, _modesLength);
for (int i = 0; i < cutpoint; i++)
{
o1.ModeGenes[i] = p2.ModeGenes[i];
}
for (int i = cutpoint; i < _modesLength; i++)
{
o1.ModeGenes[i] = ModeGenes[i];
}
}
public void Copy(ScheduleGenome c)
{
fitness = c.fitness;
for (int i = 0; i < JobGenes.Length; i++)
{
JobGenes[i] = c.JobGenes[i];
if (i < _modesLength)
{
TimeGenes[i] = c.TimeGenes[i];
ModeGenes[i] = c.ModeGenes[i];
}
}
}
public void IntializePopulations(ScheduleGenome genomeDefinition)
{
elite = new ScheduleGenome(genomeDefinition);
elite.realCrossover = realCrossover;
elite.RandomInit();
for (int i = 0; i < _popsize; i++)
{
population[i] = new ScheduleGenome(elite);
population[i].RandomInit();
//population[i] = new ScheduleGenome(length, tl, modes, mutationRate, delayRate, delayMean);
//population[i].realCrossover = realCrossover;
}
for (int i = 0; i < _offsize; i++)
{
offspring[i] = new ScheduleGenome(elite);
offspring[i].RandomInit();
//offspring[i] = new ScheduleGenome(length, tl, modes, mutationRate, delayRate, delayMean);
//offspring[i].realCrossover = realCrossover;
}
}
// todo: broken, fix.
public void SeedPopulation(int[] genes, double[] times, int[] modes, int mModes, double mutationRate)
{
population[0] = new ScheduleGenome(genes.Length, times.Length, modes.Length, mModes, mutationRate, genes, times, modes);
}
