public SimplePopulation getPopulation(BinaryString template) {
SimplePopulation pop = new SimplePopulation();
for (Individual ind : individuals) {
pop.addIndividual(ind.getSolution(template));
}
return pop;
}
// ::::::::::::::::::::::::::: Copyright(c) M@nso 2016 :::::::::::::::::::
///////////////////////////////////////////////////////////////////////////
public static void main(String[] args) {
Random rnd = new Random(1223);
SimplePopulation mp = new MultiPopulation();
mp.setParameters("500");
mp.setRandomGenerator(rnd);
Solution i = new OneMax();
i.setRandomGenerator(rnd);
i.setParameters("1000");
mp.createRandom(i);
for (int j = 0; j < mp.getNumberOfIndividuals(); j++) {
Solution i1 = mp.removeRandom();
Solution i2 = mp.removeRandom();
if (i1.compareTo(i2) > 0) {
mp.addIndividual(i1);
mp.addIndividual(i1);
} else {
mp.addIndividual(i2);
mp.addIndividual(i2);
}
}
Recombination x = new M_Uniforme();
x.setRandomGenerator(rnd);
for (int j = 0; j < mp.getNumberOfIndividuals(); j++) {
System.out.println(" i " + j);
mp = x.execute(mp);
mp.evaluate();
}
System.out.println("" + mp);
}
public SimplePopulation sampleNewPopulation(SimplePopulation pop) {
SimplePopulation newPop = pop.getCleanClone();
BinaryString template = (BinaryString) pop.getIndividual(0);
for (int i = 0; i < offspringSize; i++) {
newPop.addIndividual(generateInstance(template));
}
return newPop;
}
public static Population getPopulation(SimplePopulation pop) {
Population newPop = new SelectedSet(pop.getNumberOfIndividuals());
newPop.individuals = new Individual[pop.getNumberOfIndividuals()];
for (int i = 0; i < newPop.individuals.length; i++) {
newPop.individuals[i] = new Individual((BinaryString) pop.getIndividual(i));
}
newPop.computeUnivariateFrequencies();
return newPop;
}
@Override
public SimplePopulation execute(SimplePopulation parents) {
// clean population
SimplePopulation newPopulation = parents.getCleanClone();
Solution indiv1;
Solution indiv2;
// get list of individuals
List<Solution> pop = parents.getList(); // raw list of population (parents.pop)
int index = 0;
while (index < pop.size()) { // iterate all the individuals
// first parent
indiv1 = pop.get(index++);
if (index == pop.size() || random.nextDouble() >= pCrossover) { // insert clone
newPopulation.addIndividual(indiv1);
continue;
} // END: if
// second parent
indiv2 = pop.get(index++);
// ::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::
// -------------------- multiset recombination ----------------------
// ::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::
// number of recombinations
int numberOfRecombinations = Math.min(indiv1.getNumberOfCopies(), indiv2.getNumberOfCopies());
// insert clones of the individual with greather number of copies
if (indiv1.getNumberOfCopies() > indiv2.getNumberOfCopies()) {
Solution clone = indiv1.getClone();
clone.setNumberOfCopies(indiv1.getNumberOfCopies() - numberOfRecombinations);
newPopulation.addIndividual(clone); // add clone
} else if (indiv2.getNumberOfCopies() > indiv1.getNumberOfCopies()) {
Solution clone = indiv2.getClone();
clone.setNumberOfCopies(indiv2.getNumberOfCopies() - numberOfRecombinations);
newPopulation.addIndividual(clone); // add clone
}
double prob = 0.5;
// recombine multiset individuals
for (int nCuts = 1; nCuts <= numberOfRecombinations; nCuts++) {
// clone multiset individuals to simple individuals
Solution clone1 = indiv1.getClone();
clone1.setNumberOfCopies(1);
Solution clone2 = indiv2.getClone();
clone2.setNumberOfCopies(1);
// execute crossover
doCrossover((BinaryString) clone1, (BinaryString) clone2, prob / nCuts);
// add individuals
newPopulation.addIndividual(clone1);
newPopulation.addIndividual(clone2);
}
} // END : list
return newPopulation;
}
