private void btn_run_Click(object sender, EventArgs e)
{
if (txtBx_target.Text.Trim().Length > 0)
{
target = txtBx_target.Text.Trim();
numberOfGenes = txtBx_target.Text.Trim().Length;
maxGenerations = trkbar_maxGenerations.Value;
populationSize = trkbar_populationSize.Value;
crossoverRate = (float)trkBar_crossoverRate.Value / 100;
mutationRate = (float)trkBar_mutationRate.Value / 100;
numberOfMates = trkBar_numMates.Value;
lstBx_output.Items.Clear();
btn_run.Enabled = false;
btn_reset.Enabled = false;
btn_about.Enabled = false;
var timer = Stopwatch.StartNew();
// Initialize population
List<Individual> population = new List<Individual>();
for (int i = 0; i < populationSize; i++)
{
population.Add(new Individual());
population[i].GenerateRandomGenes(numberOfGenes, ref generator);
}
// evolve generations
int generation = 1;
while (generation <= maxGenerations)
{
// evaluate fitness
int elite = 0;
for (int i = 0; i < populationSize; i++)
{
population[i].CalculateFitness(target);
if (population[i].GetFitness() >= population[elite].GetFitness())
elite = i;
}
// display most fit individual
string result = "Generation: " + generation + "\tBest Fit: " + population[elite].GetPhenotype();
lstBx_output.Items.Add(result);
// evaluate fitness of most fit individual
if (population[elite].GetPhenotype().Equals(target))
break;
// evolve current generation
List<Individual> newPopulation = new List<Individual>();
for (int i = 0; i < populationSize; i++)
{
Evolution selection = new Evolution();
int firstParent = selection.FindParent(numberOfMates, populationSize, ref generator, population);
int secondParent = selection.FindParent(numberOfMates, populationSize, ref generator, population);
if (secondParent == firstParent)
secondParent = (secondParent + 1) % populationSize;
Individual child = selection.BreedParents(numberOfGenes, crossoverRate, population[firstParent], population[firstParent]);
child.Mutate(numberOfGenes, mutationRate, ref generator);
newPopulation.Add(child);
}
// kill off current generation
population.Clear();
population.AddRange(newPopulation);
generation++;
}
timer.Stop();
var runTime = timer.ElapsedMilliseconds;
lbl_time.Text = "Run time: " + runTime + "ms";
}
else
{
MessageBox.Show("Please enter text in the target control", "Invalid Input", MessageBoxButtons.OK, MessageBoxIcon.Exclamation);
txtBx_target.Clear();
txtBx_target.Focus();
}
btn_run.Enabled = true;
btn_reset.Enabled = true;
btn_about.Enabled = true;
}
private void btn_run_Click(object sender, EventArgs e)
{
if (txtBx_target.Text.Trim().Length > 0)
{
target = txtBx_target.Text.Trim();
numberOfGenes = txtBx_target.Text.Trim().Length;
maxGenerations = trkbar_maxGenerations.Value;
populationSize = trkbar_populationSize.Value;
crossoverRate = (float)trkBar_crossoverRate.Value / 100;
mutationRate = (float)trkBar_mutationRate.Value / 100;
numberOfMates = trkBar_numMates.Value;
lstBx_output.Items.Clear();
btn_run.Enabled = false;
btn_reset.Enabled = false;
btn_about.Enabled = false;
var timer = Stopwatch.StartNew();
// Initialize population
List <Individual> population = new List <Individual>();
for (int i = 0; i < populationSize; i++)
{
population.Add(new Individual());
population[i].GenerateRandomGenes(numberOfGenes, ref generator);
}
// evolve generations
int generation = 1;
while (generation <= maxGenerations)
{
// evaluate fitness
int elite = 0;
for (int i = 0; i < populationSize; i++)
{
population[i].CalculateFitness(target);
if (population[i].GetFitness() >= population[elite].GetFitness())
{
elite = i;
}
}
// display most fit individual
string result = "Generation: " + generation + "\tBest Fit: " + population[elite].GetPhenotype();
lstBx_output.Items.Add(result);
// evaluate fitness of most fit individual
if (population[elite].GetPhenotype().Equals(target))
{
break;
}
// evolve current generation
List <Individual> newPopulation = new List <Individual>();
for (int i = 0; i < populationSize; i++)
{
Evolution selection = new Evolution();
int firstParent = selection.FindParent(numberOfMates, populationSize, ref generator, population);
int secondParent = selection.FindParent(numberOfMates, populationSize, ref generator, population);
if (secondParent == firstParent)
{
secondParent = (secondParent + 1) % populationSize;
}
Individual child = selection.BreedParents(numberOfGenes, crossoverRate, population[firstParent], population[firstParent]);
child.Mutate(numberOfGenes, mutationRate, ref generator);
newPopulation.Add(child);
}
// kill off current generation
population.Clear();
population.AddRange(newPopulation);
generation++;
}
timer.Stop();
var runTime = timer.ElapsedMilliseconds;
lbl_time.Text = "Run time: " + runTime + "ms";
}
else
{
MessageBox.Show("Please enter text in the target control", "Invalid Input", MessageBoxButtons.OK, MessageBoxIcon.Exclamation);
txtBx_target.Clear();
txtBx_target.Focus();
}
btn_run.Enabled = true;
btn_reset.Enabled = true;
btn_about.Enabled = true;
}