/**
* As TRIBES manages an own structured set of particles (the list of Tribes containing explorers
* and memories), the setPopulation method is only telling Tribes the range of the indiviuals in
* the beginning of the run, the individuals will be discarded.
*/
public void setPopulation(Population pop) {
if (pop == null) return;
population = pop;
if (population.get(0) instanceof InterfaceDataTypeDouble) {
range = ((InterfaceDataTypeDouble) population.get(0)).getDoubleRange();
setDimension(range.length);
} else {
System.err.println(
"warning, TRIBES requires InterfaceESIndidivual instead of "
+ population.get(0).getClass()
+ ". Couldnt correctly init the problem range.");
}
}
/**
* This method allows you to merge to populations into an archive. This method will add elements
* from pop to the archive but will also remove elements from the archive if the archive target
* size is exceeded.
*
* @param pop The population that may add Individuals to the archive.
*/
public void addElementsToArchive(Population pop) {
if (pop.getArchive() == null) pop.SetArchive(new Population());
// test for each element in population if it
// is dominating a element in the archive
for (int i = 0; i < pop.size(); i++) {
if (this.isDominant((AbstractEAIndividual) pop.get(i), pop.getArchive())) {
this.addIndividualToArchive(
(AbstractEAIndividual) ((AbstractEAIndividual) pop.get(i)).clone(), pop.getArchive());
}
}
// Now clear the archive of surplus individuals
Population archive = pop.getArchive();
this.m_Cleaner.removeSurplusIndividuals(archive);
}
protected TribesExplorer positionToExplorer(TribesPosition pos) {
TribesExplorer tmp = (TribesExplorer) population.get(0);
if (tmp == null) System.err.println("Error in Tribes::positionToExplorer!");
TribesExplorer indy = tmp.clone();
indy.clearPosVel();
indy.SetDoubleGenotype(pos.getPos());
indy.SetFitness(pos.getFitness());
return indy;
}
/** This method will optimize */
public void optimize() {
AbstractEAIndividual indy;
Population original = (Population) this.m_Population.clone();
double tmpD;
InterfaceMutation tmpMut;
for (int i = 0; i < this.m_Population.size(); i++) {
indy = ((AbstractEAIndividual) this.m_Population.get(i));
tmpD = indy.getMutationProbability();
indy.setMutationProbability(1.0);
if (mutator == null) indy.mutate();
else mutator.mutate(indy);
indy.setMutationProbability(tmpD);
}
this.m_Problem.evaluate(this.m_Population);
for (int i = 0; i < this.m_Population.size(); i++) {
if (((AbstractEAIndividual) original.get(i))
.isDominatingDebConstraints(((AbstractEAIndividual) this.m_Population.get(i)))) {
this.m_Population.remove(i);
this.m_Population.add(i, original.get(i));
} else {
// else: mutation improved the individual
}
}
this.m_Population.incrGeneration();
// for (int i = 0; i < this.m_Population.size(); i++) {
// indy1 = (AbstractEAIndividual) this.m_Population.get(i);
// indy2 = (AbstractEAIndividual)(indy1).clone();
// indy2.mutate();
// this.m_Problem.evaluate((AbstractEAIndividual) indy2);
// //indy2.SetFitness(0, indy2.evaulateAsMiniBits());
// this.m_Population.incrFunctionCalls();
// //if (indy2.getFitness(0) < indy1.getFitness(0)) {
// if (indy2.isDominating(indy1)) {
// this.m_Population.remove(i);
// this.m_Population.add(i, indy2);
// }
// }
// this.m_Population.incrGeneration();
this.firePropertyChangedEvent(Population.nextGenerationPerformed);
}
