bool FlowShopOpCrossoverQuad::operator()(FlowShop & _flowshop1, FlowShop & _flowshop2)
{
bool oneAtLeastIsModified;
// computation of the 2 random points
unsigned int point1, point2;
do
{
point1 = rng.random(std::min(_flowshop1.size(), _flowshop2.size()));
point2 = rng.random(std::min(_flowshop1.size(), _flowshop2.size()));
}
while (fabs((double) point1-point2) <= 2);
// computation of the offspring
FlowShop offspring1 = generateOffspring(_flowshop1, _flowshop2, point1, point2);
FlowShop offspring2 = generateOffspring(_flowshop2, _flowshop1, point1, point2);
// does at least one genotype has been modified ?
if ((_flowshop1 != offspring1) || (_flowshop2 != offspring2))
{
// update
_flowshop1.value(offspring1);
_flowshop2.value(offspring2);
// at least one genotype has been modified
oneAtLeastIsModified = true;
}
else
{
// no genotype has been modified
oneAtLeastIsModified = false;
}
// return 'true' if at least one genotype has been modified
return oneAtLeastIsModified;
}
void MainWindow::on_FPS_clicked()
{
//initial graph
graphs gr;
gr.setModal(true);
int k = 0;
while(k < COUNT){
TotalFitness = 0;
population.clear();
newpopulation.clear();
generatePopulations(false);
//sort by fitness
sort(this->population.begin(), this->population.end(), by_fitness());
int j = 0;
while(j < COUNT){
calc_prob_ranges(false);
//offsprings
for(int i=0; i<((COUNT/2)/2); i++){
float val = randomRange(0, 1);
temp = generateOffspring(val);
offsprint_x1 = temp.x;
offsprint_y1 = temp.y;
val = randomRange(0, 1);
temp = generateOffspring(val);
offsprint_x2 = temp.x;
offsprint_y2 = temp.y;
//mutation process
mutation(offsprint_x1, offsprint_y2, offsprint_x2, offsprint_y1, false);
}
//merge new with old population
population.insert(population.end(), newpopulation.begin(), newpopulation.end());
//clear new population
newpopulation.clear();
//sort by compute
sort(population.begin(), population.end(), by_fitness());
// erase unecessary elements/population:
population.erase(population.begin()+COUNT,population.end());
//cout << "population for new iteration" << endl;
TotalFitness = 0;
for(int i=0; i < population.size(); i++ ){
TotalFitness = TotalFitness + population[i].fitness;
//cout << population[i].x << "," << population[i].y << "," << population[i].fitness << endl;
}
//best of iteration
best.push_back(population[0].fitness);
//cout << "fps best" << population[0].fitness << endl;
//avg of iteration
avg.push_back(population[(COUNT/2)-1].fitness);
j++;
}
k++;
TotalFitness = 0;
pso();
ais();
gr.data.push_back({best, avg, pso_best, ais_best, ais_avg,COUNT});
reverse(pso_best.begin(), pso_best.end());
reverse(ais_best.begin(), ais_best.end());
reverse(ais_avg.begin(), ais_avg.end());
reverse(best.begin(), best.end());
reverse(avg.begin(), avg.end());
best_best.push_back(best[0]);
avg_avg.push_back(avg[0]);
ais_avg_avg.push_back(ais_avg[0]);
pso_bb.push_back(pso_best[0]);
pso_best.clear();
ais_bb.push_back(ais_best[0]);
ais_best.clear();
ais_avg.clear();
best.clear();
avg.clear();
}
gr.data.push_back({best_best,avg_avg, pso_bb, ais_bb, ais_avg_avg,COUNT});
best_best.clear();
avg_avg.clear();
ais_bb.clear();
pso_bb.clear();
ais_avg_avg.clear();
// for(int i=0; i < COUNT; i++ ){
// gr.best.push_back({best[i].fitness});
// gr.avg.push_back({avg[i].fitness});
// }
// cout << gr.best.size() << endl;
// gr.generation = COUNT;
gr.makePlot(0);
gr.exec();
}
