public Chromosomes.IChromosome[] PerformSelection(Populations.IPopulation population, int size)
{
//Getting all of the chromosomes that are in population.
Chromosomes.IChromosome[] individuals = population.GetChromosomes();
//Calculating the number of the those chromosomes.
int sz = individuals.Length;
//Calculating the fitness of each chromosome.
double[] f = new double[sz];
double[] fitnesses = population.GetFitnesses();
for (int i = 0; i < sz; ++i)
f[i] = fitnesses[i];
//Defining the to-be-returned array.
Chromosomes.IChromosome[] ret = new Chromosomes.IChromosome[size];
//Selecting the parents from the population and putting them in ret.
for (int i = 0; i < size; ++i)
{
int parentidx=-1;
for (int j=0;j<TournamentSize;++j){
int idx=random.Next(size);
if (parentidx==-1||f[parentidx]<f[idx]){
parentidx=idx;
}
}
ret[i]=individuals[parentidx].Clone();
}
//Returning the result.
return ret;
}
public Chromosomes.IChromosome[] PerformSelection(Populations.IPopulation population, int size)
{
//Getting all of the chromosomes that are in population.
Chromosomes.IChromosome[] individuals = population.GetChromosomes ();
//Calculating the number of the those chromosomes.
int sz = individuals.Length;
//Calculating the fitness of each chromosome.
double[] f = new double[sz];
double[] fitnesses = population.GetFitnesses();
for (int i = 0; i < sz; ++i)
f[i] = fitnesses[i];
//Sorting the population by descending fitness values.
Sort (individuals, f, 0, sz - 1);
//Defining the to-be-returned array.
Chromosomes.IChromosome[] ret = new Chromosomes.IChromosome[size];
//Selecting the parents from the population and putting them in ret.
for (int i = 0; i < size; ++i)
ret[i] = individuals[i].Clone();
//Returning the result.
return ret;
}
//The mergin method.
private static void Merge(Chromosomes.IChromosome[] individuals, double[] f, int begin, int mid, int end)
{
int sz = end - begin + 1;
double[] tempF = new double[sz];
Chromosomes.IChromosome[] tempIndividuals = new Chromosomes.IChromosome[sz];
int i = begin;
int j = mid + 1;
int idx = -1;
while (true)
{
++idx;
if (f[i] <= f[j])
{
tempF[idx] = f[j];
tempIndividuals[idx] = individuals[j];
++j;
}
else
{
tempF[idx] = f[i];
tempIndividuals[idx] = individuals[i];
++i;
}
if ((i == mid + 1) || (j == end + 1))
break;
}
for (; i < mid + 1; ++i)
{
++idx;
tempF[idx] = f[i];
tempIndividuals[idx] = individuals[i];
}
for (; j < end + 1; ++j)
{
++idx;
tempF[idx] = f[j];
tempIndividuals[idx] = individuals[j];
}
for (int k = 0; k < sz; ++k)
{
f[begin + k] = tempF[k];
individuals[begin + k] = tempIndividuals[k];
}
}
public Chromosomes.IChromosome[] PerformSelection(Populations.IPopulation population, int size)
{
//Getting all of the chromosomes that are in population.
Chromosomes.IChromosome[] individuals = population.GetChromosomes();
//Calculating the number of the those chromosomes.
int sz = individuals.Length;
//Calculating the fitness of each chromosome.
double[] f = new double[sz];
double[] fitnesses = population.GetFitnesses();
for (int i = 0; i < sz; ++i)
f[i] = fitnesses[i];
//Calculating the sum of the fitnesses.
double sum = 0.0;
for (int i = 0; i < sz; ++i)
sum += f[i];
//The normalization step.
for (int i = 0; i < sz; ++i)
f[i] /= sum;
//Sorting the population by descending fitness values.
RouletteWheelSelectionMethod.Sort(individuals, f, 0, sz - 1);
//The accumulation step.
for (int i = 1; i < sz; ++i)
f[i] += f[i - 1];
f[sz - 1] = 1.0; //To ensure that the sum of all the fitnesses is equal to 1.0.
//Defining the to-be-returned array.
Chromosomes.IChromosome[] ret = new Chromosomes.IChromosome[size];
//Selecting the parents from the population and putting them in ret.
for (int i = 0; i < size; ++i)
{
int idx = RouletteWheelSelectionMethod.Find(f, RouletteWheelSelectionMethod.random.NextDouble());
ret[i] = individuals[idx].Clone();
}
//Returning the result.
return ret;
}
