bool ArtificialBeeColony::onlookerBeesPhase(StateP state, DemeP deme)
{
// jednostavni odabir, uz selFitPropOp
/* for( uint i = 0; i < deme->getSize(); i++ ) { // for each food source
// choose a food source depending on its fitness value (better individuals are more likely to be chosen)
IndividualP food = selFitOp->select(*deme);
createNewFoodSource(food, state, deme);
}
*/
// uz vjerojatnosti, jedinka po jedinka
calculateProbabilities(state, deme);
int demeSize = deme->getSize();
int i = state->getRandomizer()->getRandomInteger(demeSize);
int n = 0;
while( n < demeSize) {
int fact = i++ % demeSize;
IndividualP food = deme->at(fact);
if (state->getRandomizer()->getRandomDouble() < probability_[fact]){
n++;
createNewFoodSource(food, state, deme);
}
}
return true;
}
bool createNewFoodSource(IndividualP food, StateP state, DemeP deme)
{
//for each food source find a neighbour
IndividualP neighbour;
do{
neighbour = selRandomOp->select(*deme);
}while(food->index == neighbour->index);
//potential new food source
IndividualP newFood = copy(food);
FloatingPointP flp = boost::dynamic_pointer_cast<FloatingPoint::FloatingPoint> (food->getGenotype(0));
std::vector< double > &foodVars = flp->realValue;
flp = boost::dynamic_pointer_cast<FloatingPoint::FloatingPoint> (neighbour->getGenotype(0));
std::vector< double > &neighbourVars = flp->realValue;
flp = boost::dynamic_pointer_cast<FloatingPoint::FloatingPoint> (newFood->getGenotype(0));
std::vector< double > &newFoodVars = flp->realValue;
uint param = state->getRandomizer()->getRandomInteger((int)foodVars.size());
double factor = state->getRandomizer()->getRandomDouble();
double value = foodVars[param] * (1-2*factor)*(foodVars[param]-neighbourVars[param]);
if (value > ubound)
value = ubound;
else if (value <lbound)
value = lbound;
//produce a modification on the food source (discover a new food source)
newFoodVars[param] = value;
evaluate(newFood);
flp = boost::dynamic_pointer_cast<FloatingPoint::FloatingPoint> (food->getGenotype(1));
double &foodTrial = flp->realValue[0];
// d) if the fitness value of the new food source is better than that of the original source,
// memorize the new source, forget the old one and set trial to 0
// otherwise keep the old one and increment trial
if(newFood->fitness->isBetterThan( food->fitness) )
{
foodVars[param] = value;
evaluate(food);
foodTrial = 0;
}
else {
foodTrial +=1;
}
return true;
}
//! cross donor vectors with population members to create trial vectors
void DifferentialEvolution::crossover(DemeP deme, uint index, StateP state)
{
// get population member and corresponding donor vector
FloatingPoint::FloatingPoint* flp1 = (FloatingPoint::FloatingPoint*) (deme->at(index)->getGenotype().get());
int dim = (int) flp1->realValue.size();
FloatingPoint::FloatingPoint* flp2 = (FloatingPoint::FloatingPoint*) donor_vector[index]->getGenotype().get();
// crossover their elements (keep the result in donor_vector)
for(uint i = 0; i < flp1->realValue.size(); i++) {
if (state->getRandomizer()->getRandomDouble() <= CR_ || i == state->getRandomizer()->getRandomInteger(dim)) {
}
else {
flp2->realValue[i] = flp1->realValue[i];
}
}
}
bool hypermutationPhase(StateP state, DemeP deme, std::vector<IndividualP> &clones)
{
uint M; // M - number of mutations of a single antibody
uint k;
//sort
std::sort (clones.begin(), clones.end(), sortPopulationByFitness);
for( uint i = 0; i < clones.size(); i++ ){ // for each antibody in vector clones
IndividualP antibody = clones.at(i);
FloatingPointP flp = boost::dynamic_pointer_cast<FloatingPoint::FloatingPoint> (antibody->getGenotype(0));
std::vector< double > &antibodyVars = flp->realValue;
k = 1 + i/(dup+1);
M =(int) ((1- 1/(double)(k)) * (c*dimension) + (c*dimension));
// mutate M times
for (uint j = 0; j < M; j++){
uint param = state->getRandomizer()->getRandomInteger((int)antibodyVars.size());
double randDouble1 = state->getRandomizer()->getRandomDouble();
double randDouble2 = state->getRandomizer()->getRandomDouble();
double value = antibodyVars[param] + (1-2*randDouble1)* 0.2 * (ubound - lbound) * pow(2, -16*randDouble2 );
if (value > ubound)
value = ubound;
else if (value <lbound)
value = lbound;
//produce a mutation on the antibody
antibodyVars[param] = value;
}
FitnessP parentFitness = antibody->fitness;
evaluate(antibody);
// if the clone is better than its parent, reset clone's age
if(antibody-> fitness->isBetterThan(parentFitness)){
flp = boost::dynamic_pointer_cast<FloatingPoint::FloatingPoint> (antibody->getGenotype(1));
double &age = flp->realValue[0];
age = 0;
}
}
return true;
}