void Replace(Chromosome[] children)
{
Population nextPopulation = new Population( this, population.PopulationSize );
for(int i=0;i<populationSize;i++)
{
//
// Since the recombination record for a chromosome may contain a
// pointer to chromosome's in the previous population, it has to be
// cleared out. This prevents us from getting an unbroken reference
// chain between the current population's chromosomes all the way back
// to the first population (which would prevent the garbage collector
// from reclaiming any chromosome memory).
// (There is probably some way we can configure how deep we want
// to remember recombination records. But that might be overkill
// if we get everything serializing nicely.)
//
population.Chromosomes[i].Parents = null;
nextPopulation.Chromosomes[i] = children[i];
nextPopulation.Chromosomes[i].ID = nextChromosomeID++;
}
NewPopulationEventArgs e = new NewPopulationEventArgs();
e.OldPopulation = population;
e.NewPopulation = nextPopulation;
e.Generation = generation;
OnNewPopulation( e );
population = nextPopulation; // BUGBUG: should move this before the call out
}
/*
* mode - most frequently occuring score.
* median - midpoint of distribution, above which have of the scores fall, and below
* which the other half fall.
*/
/// <summary>
/// Creates a PopulationSummary from a Population.
/// </summary>
/// <param name="ga">The GA.</param>
/// <param name="Population">The Population for which the
/// PopulationSummary will provide summary information.
/// </param>
public PopulationSummary( GA ga, Population Population )
{
double totalObjective;
lowestObjective = System.Double.MaxValue;
highestObjective = System.Double.MinValue;
totalObjective = 0;
foreach( Chromosome c in Population.Chromosomes )
{
totalObjective += c.RawObjective;
if ( c.RawObjective < LowestObjective )
{
lowestObjective = c.RawObjective;
if ( ga.ObjectiveType == ObjectiveType.MinimizeObjective )
{
bestChromosome = c;
}
}
if ( c.RawObjective > HighestObjective )
{
highestObjective = c.RawObjective;
if ( ga.ObjectiveType == ObjectiveType.MaximizeObjective )
{
bestChromosome = c;
}
}
}
meanObjective = totalObjective / Population.Chromosomes.Length;
//
// Variance is the average squared deviation from the mean.
// Standard Deviation is just the square root of this.
//
double sum = 0;
foreach(Chromosome c in Population.Chromosomes)
{
double deviation;
double squaredDeviation;
deviation = c.RawObjective - meanObjective;
squaredDeviation = deviation * deviation;
sum += squaredDeviation;
}
variance = sum / (Population.Chromosomes.Length-1);
standardDeviation = Math.Sqrt( variance );
}
void Initialize()
{
Population = new Population( this, PopulationSize );
for(int i=0;i<PopulationSize;i++)
{
Population.Chromosomes[i] = new Chromosome();
Population.Chromosomes[i].Genes = new Gene[ChromosomeLength];
Population.Chromosomes[i].ID = nextChromosomeID++;
//GeneDescriptor geneDescriptor = geneDescriptors[0];
bool[] usedLabels = new bool[ChromosomeLength];
for(int j=0;j<ChromosomeLength;j++)
{
// if ( !Homogeneous )
// {
// geneDescriptor = geneDescriptors[j];
// }
Population.Chromosomes[i].Genes[j] = geneDescriptor.GetRandomAllele();
//
int label;
do
{
label = Utils.Rand.Next(ChromosomeLength);
}
while ( usedLabels[label] );
usedLabels[label] = true;
Population.Chromosomes[i].Genes[j].Label = label;
}
}
}
