// This function uses two fixed points for two-point crossover. For better performance these two points may be made random and/or adjusted over time
// For example, in higher generations they could be moved further to the back
public void twoFixedPointCrossover()
{
int selectionSize = Convert.ToInt32(0.4 * populationSize);
Genome parent1 = new Genome();
Genome parent2 = new Genome();
Genome child1 = new Genome();
Genome child2 = new Genome();
int r;
int fixpoint1 = 4;
int fixpoint2 = 15;
for (int i = selectionSize; i < populationSize; i++)
{
// Randomly selects first parent
r = Variables.getRandomInt(0, selectionSize);
parent1 = oldPopulation[r].Genome;
// Randomly selects second parent
r = Variables.getRandomInt(0, selectionSize);
parent2 = oldPopulation[r].Genome;
for (int j = 0; j < 20; j++)
{
// Case 1: fixpoint 1 to fixpoint 2, fixpoints exclusive
if (j > fixpoint1 && j < fixpoint2)
{
// Iterates over the eight-bit-blocks and adds all bits to the respective parent
for (int k = j * 8; k < j * 8 + 8; k++)
{
child1.Genome1.Set(k, parent1.Genome1.Get(k));
child2.Genome1.Set(k, parent2.Genome1.Get(k));
}
}
// Case 2: Before fixpoint 1 and after fixpoint 2, fixpoints inclusive
else
{
// Iterates over the eight-bit-blocks and adds all bits to the respective parent
for (int k = j * 8; k < j * 8 + 8; k++)
{
child1.Genome1.Set(k, parent2.Genome1.Get(k));
child2.Genome1.Set(k, parent1.Genome1.Get(k));
}
}
}
Genome.genomeToPath(child1);
population[i] = new Population(Variables.path, child1, 0, false, false);
// Counts up since we are adding 2 children per iteration, not just one
i++;
// If we are not yet at maximum (which could happen due to double->int conversion) we add the second child too
if (i < populationSize)
{
Genome.genomeToPath(child2);
population[i] = new Population(Variables.path, child2, 0, false, false);
}
}
}
// This function uses single-bit Uniform Crossover.
public void singleBitCrossover()
{
// Size of current new generation is 40% of old generation (before crossover)
int selectionSize = Convert.ToInt32(0.4 * populationSize);
int r;
Genome parent1 = new Genome();
Genome parent2 = new Genome();
Genome mask = new Genome();
Genome child1 = new Genome();
Genome child2 = new Genome();
// Iterates from selection Size (current maximum of the new population) to population size, the wanted maximum. That means 60% come from crossover
for (int i = selectionSize; i < populationSize; i++)
{
// Randomly selects first parent
r = Variables.getRandomInt(0, selectionSize);
parent1 = oldPopulation[r].Genome;
// Randomly selects second parent
r = Variables.getRandomInt(0, selectionSize);
parent2 = oldPopulation[r].Genome;
// Crates a random mask genome. This function sucks.
mask = new Genome(true);
// Generates children
for (int j = 0; j < 160; j++)
{
if (mask.Genome1.Get(j))
{
// If mask(i) is 1 then child1 gets the value at that point from parent1, child2 from parent2
child1.Genome1.Set(j, parent1.Genome1.Get(j));
child2.Genome1.Set(j, parent2.Genome1.Get(j));
}
else
{
// If mask(i) is 0 then child1 gets the value at that point from parent2, child2 from parent1
child1.Genome1.Set(j, parent2.Genome1.Get(j));
child2.Genome1.Set(j, parent1.Genome1.Get(j));
}
}
// Adds the genome and its corresponding path to the population at position i. Also sets Selected to false.
Genome.genomeToPath(child1);
population[i] = new Population(Variables.path, child1, 0, false, false);
// Counts up since we are adding 2 children per iteration, not just one
i++;
// If we are not yet at maximum (which could happen due to double->int conversion) we add the second child too
if (i < populationSize)
{
Genome.genomeToPath(child2);
population[i] = new Population(Variables.path, child2, 0, false, false);
}
}
}
private void button_genomeToPath_Click(object sender, EventArgs e)
{
Genome genome = new Genome();
char[] text = this.textBox1.Text.ToCharArray();
for (int i = 0; i < 160; i++)
{
if (text[i] == '1')
{
genome.Genome1.Set(i, true);
}
}
Genome.genomeToPath(genome);
this.glControl1.Refresh();
}
// This function uses genomePart Uniform Crossover. It works like a crossover function but uses a significantly shorter mask genome
// because it always chooses an entire 8bit block
public void eightBitCrossover()
{
// Size of current new generation is 40% of old generation (before crossover)
int selectionSize = Convert.ToInt32(0.4 * populationSize);
int r;
Genome parent1 = new Genome();
Genome parent2 = new Genome();
bool[] mask;
Genome child1 = new Genome();
Genome child2 = new Genome();
// Iterates from selection Size (current maximum of the new population) to population size, the wanted maximum. That means 60% come from crossover
for (int i = selectionSize; i < populationSize; i++)
{
// Randomly selects first parent
r = Variables.getRandomInt(0, selectionSize);
parent1 = oldPopulation[r].Genome;
// Randomly selects second parent
r = Variables.getRandomInt(0, selectionSize);
parent2 = oldPopulation[r].Genome;
// Crates a random mask genome in form of a char[]. char[] is much faster than bool[], genome or bitarray and for our purpose the format doesn't matter
mask = GenomePart.getRandomGenome();
for (int j = 0; j < 20; j++)
{
// Checks the mask
if (mask[j])
{
// If mask == 1 then the i'th 8bit block will be selected from parent1 for child1 and from parent2 for child2
// k = j*8 since every position in the mask genome covers 8 positions in the actual genome
for (int k = j * 8; k < j * 8 + 8; k++)
{
child1.Genome1.Set(k, parent1.Genome1.Get(k));
child2.Genome1.Set(k, parent2.Genome1.Get(k));
}
}
else
{
// If mask == 0 then the i'th 8bit block will be selected from parent1 for child2 and from parent2 for child1
// k = j*8 since every position in the mask genome covers 8 positions in the actual genome
for (int k = j * 8; k < j * 8 + 8; k++)
{
child1.Genome1.Set(k, parent2.Genome1.Get(k));
child2.Genome1.Set(k, parent1.Genome1.Get(k));
}
}
}
Genome.genomeToPath(child1);
population[i] = new Population(Variables.path, child1, 0, false, false);
// Counts up since we are adding 2 children per iteration, not just one
i++;
// If we are not yet at maximum (which could happen due to double->int conversion) we add the second child too
if (i < populationSize)
{
Genome.genomeToPath(child2);
population[i] = new Population(Variables.path, child2, 0, false, false);
}
}
}