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package jcgp.backend.modules.ea;
import jcgp.backend.modules.mutator.Mutator;
import jcgp.backend.population.Population;
import jcgp.backend.resources.Resources;
import jcgp.backend.resources.parameters.BooleanParameter;
import jcgp.backend.resources.parameters.IntegerParameter;
import jcgp.backend.resources.parameters.Parameter;
import jcgp.backend.resources.parameters.ParameterStatus;
/**
* (μ + λ) EA.
*
*
* @author Eduardo Pedroni
*
*/
public class MuPlusLambda implements EvolutionaryAlgorithm {
private int fittestChromosome;
private IntegerParameter parents, offspring;
private BooleanParameter report;
public MuPlusLambda(final Resources resources) {
parents = new IntegerParameter(1, "Parents") {
@Override
public void validate(int newValue) {
if (newValue + offspring.get() != resources.getInt("popSize")) {
status = ParameterStatus.INVALID;
status.setDetails("Parents + offspring must equal population size.");
} else if (newValue <= 0) {
status = ParameterStatus.INVALID;
status.setDetails("EA needs at least 1 parent.");
} else {
status = ParameterStatus.VALID;
}
}
};
offspring = new IntegerParameter(4, "Offspring") {
@Override
public void validate(int newValue) {
if (newValue + parents.get() != resources.getInt("popSize")) {
status = ParameterStatus.INVALID;
status.setDetails("Parents + offspring must equal population size.");
} else if (newValue <= 0) {
status = ParameterStatus.INVALID;
status.setDetails("EA needs at least 1 offspring.");
} else {
status = ParameterStatus.VALID;
}
}
};
report = new BooleanParameter(false, "Report") {
@Override
public void validate(boolean newValue) {
// nothing
}
};
}
@Override
public void evolve(Population population, Mutator mutator, Resources resources) {
// select fittest chromosomes
fittestChromosome = 0;
for (int i = 1; i < resources.getInt("popSize"); i++) {
if (population.getChromosome(i).getFitness() >= population.getChromosome(fittestChromosome).getFitness()) {
fittestChromosome = i;
}
}
// create copies of fittest chromosome, mutate them
for (int i = 0; i < resources.getInt("popSize"); i++) {
if (i != fittestChromosome) {
population.copyChromosome(fittestChromosome, i);
mutator.mutate(population.getChromosome(i), resources);
}
}
}
@Override
public int getFittestChromosome() {
return fittestChromosome;
}
@Override
public Parameter[] getLocalParameters() {
return new Parameter[] {parents, offspring, report};
}
@Override
public String toString() {
return "(μ + λ)";
}
}
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