bool operator () ( const individual & i1, const individual & i2 ) const
{
bool feas1 = i1.is_feasible(),
feas2 = i2.is_feasible();
if ( feas1 && !feas2 ) return true;
else if ( feas2 && !feas1 ) return false;
else if ( i1.rank < i2.rank ) return true;
else if ( i2.rank < i1.rank ) return false;
else if ( i2.crowding < i1.crowding ) return true;
else if ( i1.crowding < i2.crowding ) return false;
else return false;
}
float evaluate(individual ind){
float Fc =0 ;
std::vector<float> v = ind.getFeatureVector();
for(unsigned int i=0;i<v.size();i++){
Fc += v[i]*v[i];
}
return Fc;
}
/**
* Asexual reproduction:
*
* I just randomly chose features of one or the other parent by a probabillity proportional
* to the parents fitness function
*
* The combination strategy is used in the make offspring method to create a child.
*/
individual individual::combine1(individual indiv){
//individual child(indiv.getFeatureVector());
std::vector<float> fv;
std::vector<float> indivFV(indiv.getFeatureVector());
std::uniform_real_distribution<> dint(0,1);
float O1 = this->getObjectiveFunction();
float O2 = indiv.getObjectiveFunction();
float fittnessBias = O1>O2 ? 0.75 : 0.25;
for(unsigned int i=0;i<ndim;i++){
indivFV.at(i) = dint(this->rngEngine)<fittnessBias ? (this->featureVector).at(i) : (indiv.getFeatureVector()).at(i);
}
return individual(fv);
}
individual combine(individual i1, individual i2){
std::cerr<<"Warning: for sex aware objective function set the sexAware \n "
<<"boolean flag of the combination strategy to true! Otherwise\n"
<<" the sex of the individual has no effect."<<std::endl;
std::vector<std::pair<float, float> > newGenotype(i2.getNdim());
/* the get chromosome method gives a random selection of allele genes
* which is not neccesarrily the gene sequence that has been represented in the
* phenotype of the individual!
*
* This simulates the process of meiosis - an integral part of
* sexual reproduction.
*
* Possible improvements could inlcude gene methylation simulation and other
* acquired genetic traits other than simple mutation.
*
* When the strategy is sex aware the returned individual is returned with the objective function
* already calculated in order to reduce the number of objective function calculations.
*
* The objective function value of the male individual is estimated as
* the best objective function of his mother. That allows for possible hidden beneficial traits to
* pass to next generations and not wiped out by evolutionary pressure.
*
*/
std::vector<float > v1 = i1.getChromosome();
std::vector<float > v2 = i2.getChromosome();
std::uniform_real_distribution<float> dre(0.0,1.0);
assert(REset == true);
for(unsigned int i=0;i<i1.getNdim();i++){
float rn = dre(re);
std::pair<float, float> newGene;
newGene.first = rn>0.5?v1.at(i):v2.at(i);
newGene.second = rn>0.5?v2.at(i):v1.at(i); // saving the non expressed genes in the non expressed chromosome
//Mutation in reality is most probable to happen during meiosis - here it goes:
if(MRSet){
//std::cout<<"mutating gene gene after recombination"<<std::endl;
float rn2 = dre(re);
newGene.first += (0.5-rn2)*mutRates.at(i);
newGene.second += (0.5-rn2)*mutRates.at(i);
}
newGenotype.at(i) = newGene;
}
individual indd(newGenotype);
indd.setSex(dre(re)>0.5?MALE:FEMALE);
if(sexAware){
if(indd.getSex()==MALE){
/*
* If the created individual is a Male (objective function should not be calculated) then
* he inherits the objective function of his mother in order to reduce the objective function calcu
* lations and increase population variability. Hopefully beneficial genes are surviving generations
* when they are part of less fit individuals that way.
*/
indd.setEstimatedObjectiveFunction(i1.getSex()==FEMALE?i1.getObjectiveFunction():i2.getObjectiveFunction());
}
}
return indd;
}
float evaluate(individual ind){
return giveOF(ind.getFeatureVector());
}
