bool NetworkPNL::AddArc(int nodeFrom, int nodeTo)
{
MarkCallFunction("AddArc", true);
Graph().AddArc(nodeFrom, nodeTo);
std::vector<int> parents;
GetParents(nodeTo, parents);
Distributions().Setup(nodeTo);
m_aNodeValueStatus[nodeTo] = NetConst::NotUpdated;
return true;
}
bool GenAlgo::Run(const int func_no)
{
int nPopu,
totGen,
indx_f = 0, //Index of one parent.
indx_m = 0; //Index of another parent.
bool rslt;
func_num = func_no;
/*INPUT PARAMETERS FROM USER*/
rslt = InputParams();
totGen = nGEN;
Fitness_Calculations = 0; //Setting the fittness calculations count to 0.
/*INITIALIZE THE 0TH GEN POPULATION*/
Initialize();
Fitness_Calculations += nPOPU;
do
{
CHILDREN child1, child2; //This are used to store the children temporaryly
nPopu = nPOPU;
//ShowPopu();
if (Fitness_Calculations > MaxFitness_Calculations) break; //Maximum number of fittness calculations has occured.
while ((nPopu -= 2) >= 0)
{
/*allocation memory*/
child1.fChromo = new char[lenChromo_tot];
child2.fChromo = new char[lenChromo_tot];
child1.fFitness = child2.fFitness = NULL;
/*SELECT PARENTS*/
GetParents(&indx_f, &indx_m);
/*DO CROSSOVER*/
CreateChildren(child1, child2, &indx_f, &indx_m);
/*MUTATES THE CHILDREN*/
MutateChildren(child1);
MutateChildren(child2);
/*CALCULATE FITNESS OF OFFSPRINGS*/
child1.fFitness = CalculateFitness(child1);
child2.fFitness = CalculateFitness(child2);
Fitness_Calculations += 2;
/*IDENTIFY GOOD CHILDS AND STORE THEM*/
IdentifyChilds(child1, child2, indx_f, indx_m, nPOPU - nPopu - 2);
/*cleaning up*/
indx_f = indx_m;
delete[] child1.fChromo;
delete[] child2.fChromo;
child1.fFitness = child2.fFitness = NULL;
}
/*UPDATE NEW GEN POPULATION*/
CopyPopulation(nGEN - totGen);
std::cout << "\nGen no :: " << nGEN - totGen << std::endl;
std::cout << "**************" << std::endl;
ShowDude();
} while (--totGen);
ShowStatistics();
ShowDude();
return true;
}
