/**
* Creates a new population by recombining the parents to create children. Selects the parents to stay in the new population with roulette wheel selection.
* @see ParentRecombination()
*/
Population RefreshPopulation(Population population, ConnectedBlocksGraph connectedBlocks, GeneticOptions geneticOptions, Random random)
{
RouletteWheelSelection rouletteWheelSelection = new RouletteWheelSelection();
int childrenAmount = (int)(geneticOptions.PopulationSize * geneticOptions.PopulationRefreshing);
Individual[] children = new Individual[geneticOptions.PopulationSize];
for (int i = 0; i < childrenAmount; i++)
{
int[,] parents = ParentSelection(population, random);
children[i] = ParentRecombination(new Individual(Util.GetRow(parents, 0)), new Individual(Util.GetRow(parents, 1)), random);
children[i].CalculateFitness(connectedBlocks, geneticOptions);
}
for (int i = 0; i < geneticOptions.PopulationSize - childrenAmount; i++)
{
children[i + childrenAmount] = population.Individuals[rouletteWheelSelection.Selection(population.GetFitness(), random)];
}
return(new Population(children));
}
/**
* A method that selects two different parents to be used for recombination.
* @return A 2D array containing each parent in each row.
*/
int[,] ParentSelection(Population population, Random random)
{
RouletteWheelSelection rouletteWheelSelection = new RouletteWheelSelection();
//Select two parents with roulette wheel selection
int[,] selectedParents = new int[2, population.Individuals[0].Sequence.Length];
int firstParentPosition = rouletteWheelSelection.Selection(population.GetFitness(), random);
int secondParentPosition = rouletteWheelSelection.Selection(population.GetFitness(), random);
//Ensure that the two parents are different
while (firstParentPosition == secondParentPosition)
{
secondParentPosition = rouletteWheelSelection.Selection(population.GetFitness(), random);
}
//Add parents in list to return
for (int i = 0; i < population.Individuals[0].Sequence.Length; i++)
{
selectedParents[0, i] = population.Individuals[firstParentPosition].Sequence[i];
selectedParents[1, i] = population.Individuals[secondParentPosition].Sequence[i];
}
return(selectedParents);
}