public void startCrossover() {
for (int i = 0; i < popSize; i++) {
// test the probability is larger than crossoverRate.
if (Math.random() <= crossoverRate) {
int cutPoint = (int) (Math.random() * chromosomeLength);
// to get the other chromosome to crossover
int index2 = getCrossoverChromosome(i);
copyElements(i, index2, cutPoint);
copyElements(index2, i, cutPoint);
}
}
}
/**
* To get the other chromosome to crossover.
*
* @param index The index of original chromosome.
* @return
*/
public final int getCrossoverChromosome(int index) {
int index2 = (int) (Math.random() * popSize);
if (index == index2) {
index2 = getCrossoverChromosome(index);
}
return index2;
}
private int[] generateRandomVector() {
int vector1[] = new int[chromosomeLength];
for (int i = 0; i < chromosomeLength; i++) {
if (Math.random() > 0.5) {
vector1[i] = 1;
} else {
vector1[i] = 0;
}
}
return vector1;
}
public void startCrossover() {
calcAdaptiveParameter();
for (int i = 0; i < popSize; i++) {
if (originalPop.getFitness(i) < avgFitness) {
crossoverRate = k1 * (newPop.getFitness(i) - minFitness) / (avgFitness - minFitness);
} else {
crossoverRate = k3;
}
// test the probability is larger than crossoverRate.
if (Math.random() <= crossoverRate) {
// to get the other chromosome to crossover
int index2 = getCrossoverChromosome(i);
int vector1[] = generateRandomVector();
copyElements(i, index2, vector1);
copyElements(index2, i, vector1);
}
}
}
