/**
* Runs of the SMPSO algorithm.
* @return a <code>SolutionSet</code> that is a set of non dominated solutions
* as a result of the algorithm execution
*/
SolutionSet * PSO::execute() {
initParams();
success_ = false;
globalBest_ = NULL;
//->Step 1 (and 3) Create the initial population and evaluate
for (int i = 0; i < particlesSize_; i++) {
Solution * particle = new Solution(problem_);
problem_->evaluate(particle);
evaluations_ ++;
particles_->add(particle);
if ((globalBest_ == NULL) || (particle->getObjective(0) < globalBest_->getObjective(0))) {
if (globalBest_!= NULL) {
delete globalBest_;
}
globalBest_ = new Solution(particle);
}
}
//-> Step2. Initialize the speed_ of each particle to 0
for (int i = 0; i < particlesSize_; i++) {
speed_[i] = new double[problem_->getNumberOfVariables()];
for (int j = 0; j < problem_->getNumberOfVariables(); j++) {
speed_[i][j] = 0.0;
}
}
//-> Step 6. Initialize the memory of each particle
for (int i = 0; i < particles_->size(); i++) {
Solution * particle = new Solution(particles_->get(i));
localBest_[i] = particle;
}
//-> Step 7. Iterations ..
while (iteration_ < maxIterations_) {
int * bestIndividualPtr = (int*)findBestSolution_->execute(particles_);
int bestIndividual = *bestIndividualPtr;
delete bestIndividualPtr;
computeSpeed(iteration_, maxIterations_);
//Compute the new positions for the particles_
computeNewPositions();
//Mutate the particles_
//mopsoMutation(iteration_, maxIterations_);
//Evaluate the new particles_ in new positions
for (int i = 0; i < particles_->size(); i++) {
Solution * particle = particles_->get(i);
problem_->evaluate(particle);
evaluations_ ++;
}
//Actualize the memory of this particle
for (int i = 0; i < particles_->size(); i++) {
//int flag = comparator_.compare(particles_.get(i), localBest_[i]);
//if (flag < 0) { // the new particle is best_ than the older remember
if ((particles_->get(i)->getObjective(0) < localBest_[i]->getObjective(0))) {
Solution * particle = new Solution(particles_->get(i));
delete localBest_[i];
localBest_[i] = particle;
} // if
if ((particles_->get(i)->getObjective(0) < globalBest_->getObjective(0))) {
Solution * particle = new Solution(particles_->get(i));
delete globalBest_;
globalBest_ = particle;
} // if
}
iteration_++;
}
// Return a population with the best individual
SolutionSet * resultPopulation = new SolutionSet(1);
int * bestIndexPtr = (int *)findBestSolution_->execute(particles_);
int bestIndex = *bestIndexPtr;
delete bestIndexPtr;
cout << "Best index = " << bestIndex << endl;
Solution * s = particles_->get(bestIndex);
resultPopulation->add(new Solution(s));
// Free memory
deleteParams();
return resultPopulation;
} // execute
/**
* Runs of the SMPSO algorithm.
* @return a <code>SolutionSet</code> that is a set of non dominated solutions
* as a result of the algorithm execution
*/
SolutionSet *SMPSOhv::execute() {
initParams();
success = false;
//->Step 1 (and 3) Create the initial population and evaluate
for (int i = 0; i < swarmSize; i++){
Solution *particle = new Solution(problem_);
problem_->evaluate(particle);
problem_->evaluateConstraints(particle);
particles->add(particle);
}
//-> Step2. Initialize the speed of each particle to 0
for (int i = 0; i < swarmSize; i++) {
speed[i] = new double[problem_->getNumberOfVariables()];
for (int j = 0; j < problem_->getNumberOfVariables(); j++) {
speed[i][j] = 0.0;
}
}
// Step4 and 5
for (int i = 0; i < particles->size(); i++){
Solution *particle = new Solution(particles->get(i));
if (leaders->add(particle) == false){
delete particle;
}
}
//-> Step 6. Initialize the memory of each particle
for (int i = 0; i < particles->size(); i++){
Solution *particle = new Solution(particles->get(i));
best[i] = particle;
}
//Crowding the leaders_
//distance->crowdingDistanceAssignment(leaders, problem_->getNumberOfObjectives());
leaders->computeHVContribution();
//-> Step 7. Iterations ..
while (iteration < maxIterations) {
//Compute the speed_
computeSpeed(iteration, maxIterations);
//Compute the new positions for the particles_
computeNewPositions();
//Mutate the particles_
mopsoMutation(iteration,maxIterations);
//Evaluate the new particles in new positions
for (int i = 0; i < particles->size(); i++){
Solution *particle = particles->get(i);
problem_->evaluate(particle);
problem_->evaluateConstraints(particle);
}
//Update the archive
for (int i = 0; i < particles->size(); i++) {
Solution *particle = new Solution(particles->get(i));
if (leaders->add(particle) == false) {
delete particle;
}
}
//Update the memory of this particle
for (int i = 0; i < particles->size(); i++) {
int flag = dominance->compare(particles->get(i), best[i]);
if (flag != 1) { // the new particle is best_ than the older remembered
Solution *particle = new Solution(particles->get(i));
delete best[i];
best[i] = particle;
}
}
iteration++;
}
// Build the solution set result
SolutionSet * result = new SolutionSet(leaders->size());
for (int i=0;i<leaders->size();i++) {
result->add(new Solution(leaders->get(i)));
}
// Free memory
deleteParams();
return result;
} // execute
