public SelectedSet select(Population population) {
int N = population.getN();
int picked, maxPos;
double maxFit, currentFit;
SelectedSet selectedSet = new SelectedSet(NS); // Initialize an empty population of size NS.
for (int i = 0; i < NS; i++) {
picked = PORTFOLIO.random.nextInt(N); // Random int between 0 and N-1.
maxFit = population.getFitness(picked);
maxPos = picked;
for (int j = 1; j < tourSize; j++) {
picked = PORTFOLIO.random.nextInt(N);
currentFit = population.getFitness(picked);
if (currentFit > maxFit) {
maxFit = currentFit;
maxPos = picked;
}
}
selectedSet.setIndividual(i, population.individuals[maxPos], maxFit);
}
// selectedSet.computeFitnessStatistics();
selectedSet
.computeUnivariateFrequencies(); // NOTE!! Class Subset is responsible for computing all
// frequencies!
return selectedSet;
} // END: select(...)
public SelectedSet select(Population population) {
int N = population.getN();
SelectedSet selectedSet = new SelectedSet(NS); // Initialize an empty population.
int k = N / tourSize; // Number of tournaments within each shuffle.
int ks = NS / k; // Number of shuffles with exactly 'k' tournaments.
int rs = NS % k; // Number of tournaments within the last shuffle.
int ls = ks * k; // Order of the first selection in the last shuffle. We have NS = ls + rs.
int maxPos = 0;
for (int i = 0; i < ks; i++) {
int pos = i * k; // Position of the next selected individual.
int[] numbers = shuffle(N);
for (int j = 0; j < k * tourSize; j += tourSize) {
maxPos = tourSelect(population, selectedSet, numbers, j);
selectedSet.setIndividual(
pos++, population.individuals[maxPos], population.getFitness(maxPos));
}
}
int[] numbers = shuffle(N);
for (int j = 0; j < rs * tourSize; j += tourSize) {
maxPos = tourSelect(population, selectedSet, numbers, j);
selectedSet.setIndividual(
ls++, population.individuals[maxPos], population.getFitness(maxPos));
}
// selectedSet.computeFitnessStatistics();
selectedSet.computeUnivariateFrequencies(); // NOTE!! This is not necessary for SGA!
return selectedSet;
} // END: select(..).
public SelectedSet select(Population population) {
int N = population.getN();
sortedPopulation = new PosFit[N];
for (int i = 0; i < N; i++) sortedPopulation[i] = new PosFit(i, population.getFitness(i));
Arrays.sort(sortedPopulation); // Sort population in ascending order of fitness.
SelectedSet selectedSet = new SelectedSet(NS);
for (int i = 0; i < NS; i++) {
int best = i + N - NS;
int position = sortedPopulation[best].getPosition();
double fitness = sortedPopulation[best].getFitness();
selectedSet.setIndividual(i, population.individuals[position], fitness);
}
// selectedSet.computeFitnessStatistics();
selectedSet
.computeUnivariateFrequencies(); // NOTE!! Class Subset is responsible for computing all
// frequencies!
return selectedSet;
}