AnnealingGA.cpp

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#include "AnnealingGA.h"
#include <cmath>

#include "miscfunc.h"

#ifdef _OPENMP
#include <omp.h>
#endif

using namespace std;
using namespace gplib;
AnnealingGA::AnnealingGA(GeneralPropagation* const LocalPropagation, GeneralPopulation* const LocalPopulation, 
                GeneralTranscribe* const LocalTranscribe, const tObjectiveVector &IndObjective):
GeneralGA(LocalPropagation,LocalPopulation,LocalTranscribe,IndObjective),
InitTemperature(1.0),
AnnealingGeneration(1),
AnnealingRatio(1.0)
{
}

AnnealingGA::~AnnealingGA()
{}

int AnnealingGA::GetBestIndex()
{
        return distance(Population->GetProbabilities().begin(),max_element(Population->GetProbabilities().begin(),Population->GetProbabilities().end()));
}

void AnnealingGA::SetParams(const double InitT, const int AnnealG, const double AnnealR)
{
        InitTemperature = InitT;
        AnnealingGeneration = AnnealG;
        AnnealingRatio = AnnealR;
}

void AnnealingGA::CalcProbabilities(const int iterationnumber, rmat &LocalMisFit, GeneralPopulation &LocalPopulation)
{
        double sum = 0;
        const int popsize = LocalPopulation.GetPopsize();
        double T = 1.0;
        gplib::rvec CurrentMisFit;
        tprobabilityv Probabilities(popsize);
        // The temperature depends on the iteration
        if (iterationnumber < AnnealingGeneration)
                        T = InitTemperature;
                else 
                        T = InitTemperature / AnnealingRatio;
        // for all members of the population
        for (int  i = 0; i < popsize; ++i)
        {
                CurrentMisFit = column(LocalMisFit,i); //Get the misfit vector of the current member
                Probabilities(i) = exp(-ublas::sum(CurrentMisFit)/T); //apply the annealing scheme to the summed misfits
                sum += Probabilities(i); // add all misfit values
        }
        const double factor = 1./sum;
        for (int  i = 0; i < popsize; ++i)
                Probabilities(i) *= factor;
        LocalPopulation.SetProbabilities(Probabilities);
}

void AnnealingGA::Elitism(const int iterationnumber)
{
}

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