private void GA_Simple_Button_Click(object sender, RoutedEventArgs e)
{
GSA.GA.Algorithm.UniformRate = Double.Parse(CrossOverProbTextBox.Text);
GSA.GA.Algorithm.MutationRate = Double.Parse(MutationProbTextBox.Text);
GSA.GA.Algorithm.TournamentSize = Int32.Parse(TournamentSizeTextBox.Text);
GSA.GA.Algorithm.Elitism = ElitismCheckBox.IsChecked.Value;
GSA.GA.Algorithm.Rnd = new Random();
LogTextBox log = new GSA.LogTextBox(LogTextBox);
String solutionSelected = SolutionTextBox.Text;
if (validateSol(solutionSelected))
{
GSA.GA.FitnessCalc.setSolution(solutionSelected);
GSA.GA.Population myPop = new GSA.GA.Population(50, true);
int generationCount = 0;
while (myPop.getFittest().getFitness() < GSA.GA.FitnessCalc.getMaxFitness())
{
generationCount++;
log.Write("Generation: " + generationCount + " Fittest: " + myPop.getFittest().getFitness(), Brushes.Yellow);
myPop = GSA.GA.Algorithm.evolvePopulation(myPop);
}
log.Write("Solution found!", Brushes.GreenYellow);
log.Write("Generation: " + generationCount);
log.Write("Genes:");
log.Write(myPop.getFittest().ToString());
}
else
{
log.Write("La solución no es válida, recuerda: 64 bits de 0 y 1", Brushes.Red);
}
scrollEl.ScrollToBottom();
}
private void performAlgorithm(int maxOrMin)
{
GSA.GAMax.Algorithm.UniformRate = Double.Parse(MaxCrossOverProbTextBox.Text);
GSA.GAMax.Algorithm.MutationRate = Double.Parse(MaxMutationProbTextBox.Text);
GSA.GAMax.Algorithm.Elitism = MaxElitismCheckBox.IsChecked.Value;
GSA.GAMax.Algorithm.DieFactor = DieFactorCheckBox.IsChecked.Value;
GSA.GAMax.Algorithm.Rnd = new Random();
GSA.GAMax.Individual.Rnd = new Random();
GSA.GAMax.Algorithm.bestSolution = null;
LogTextBox log = new GSA.LogTextBox(LogTextBox);
log.Write("Constants setted", Brushes.BlueViolet);
GSA.GAMax.Individual.setDefaultGeneLength(int.Parse(BinaryLengthTextBox.Text));
GSA.GAMax.Population maxPop = new GSA.GAMax.Population(int.Parse(PopulationNumberTextBox.Text), true);
GSA.GAMax.FitnessCalc._op = (GSA.GAMax.Operation)maxOrMin;
if (GSA.GAMax.FitnessCalc.setFunctionToOperate(FormulaTextBox.Text))
{
log.Write(String.Format("Function setted: {0}", GSA.GAMax.FitnessCalc._exp.ParsedExpression.ToString()), Brushes.Azure);
//setear población
log.Write("Initial population, size: " + maxPop.size().ToString(), Brushes.Turquoise);
for (int i = 0; i < maxPop.size(); i++)
{
log.Write(maxPop.getIndividual(i).ToString(), Brushes.Wheat);
}
}
else
{
log.Write(String.Format("Your function has errors: {0}", GSA.GAMax.FitnessCalc._exp.Error), Brushes.PaleVioletRed);
log.Write("The function must be correct and contains an 'x' between []. Example 'Pow([x], 3) + 5*[x] - 2 / ([x]+2)", Brushes.PaleVioletRed);
}
int generationCount = 0;
int MaxGeneration = int.Parse(MaxIterationsTextBox.Text);
while (generationCount < MaxGeneration)
{
generationCount++;
//log.Write("Generation: " + generationCount + " Fittest: " + myPop.getFittest().getFitness(), Brushes.Yellow);
GSA.GAMax.FitnessCalc.CurrentPopulation = maxPop;
maxPop = GSA.GAMax.Algorithm.evolvePopulation(maxPop);
}
log.Write("Best Solution found!", Brushes.GreenYellow);
log.Write("Generation: " + generationCount);
log.Write("Genes:");
GSA.GAMax.Individual bestSolutionFound = GSA.GAMax.FitnessCalc.getFittest();
if (!GSA.GAMax.Algorithm.betterFitness(GSA.GAMax.Algorithm.bestSolution, bestSolutionFound))
{
bestSolutionFound = GSA.GAMax.Algorithm.bestSolution;
}
log.Write(bestSolutionFound.ToString());
}
private void GA_Simple_Button_Click(object sender, RoutedEventArgs e)
{
GSA.GA.Algorithm.UniformRate = Double.Parse(CrossOverProbTextBox.Text);
GSA.GA.Algorithm.MutationRate = Double.Parse(MutationProbTextBox.Text);
GSA.GA.Algorithm.TournamentSize = Int32.Parse(TournamentSizeTextBox.Text);
GSA.GA.Algorithm.Elitism = ElitismCheckBox.IsChecked.Value;
GSA.GA.Algorithm.Rnd = new Random();
LogTextBox log = new GSA.LogTextBox(LogTextBox);
String solutionSelected = SolutionTextBox.Text;
if (validateSol(solutionSelected)) {
GSA.GA.FitnessCalc.setSolution(solutionSelected);
GSA.GA.Population myPop = new GSA.GA.Population(50, true);
int generationCount = 0;
while (myPop.getFittest().getFitness() < GSA.GA.FitnessCalc.getMaxFitness()) {
generationCount++;
log.Write("Generation: " + generationCount + " Fittest: " + myPop.getFittest().getFitness(), Brushes.Yellow);
myPop = GSA.GA.Algorithm.evolvePopulation(myPop);
}
log.Write("Solution found!", Brushes.GreenYellow);
log.Write("Generation: " + generationCount);
log.Write("Genes:");
log.Write(myPop.getFittest().ToString());
} else {
log.Write("La solución no es válida, recuerda: 64 bits de 0 y 1", Brushes.Red);
}
scrollEl.ScrollToBottom();
}
private void performAlgorithm(int maxOrMin)
{
GSA.GAMax.Algorithm.UniformRate = Double.Parse(MaxCrossOverProbTextBox.Text);
GSA.GAMax.Algorithm.MutationRate = Double.Parse(MaxMutationProbTextBox.Text);
GSA.GAMax.Algorithm.Elitism = MaxElitismCheckBox.IsChecked.Value;
GSA.GAMax.Algorithm.DieFactor = DieFactorCheckBox.IsChecked.Value;
GSA.GAMax.Algorithm.Rnd = new Random();
GSA.GAMax.Individual.Rnd = new Random();
GSA.GAMax.Algorithm.bestSolution = null;
LogTextBox log = new GSA.LogTextBox(LogTextBox);
log.Write("Constants setted", Brushes.BlueViolet);
GSA.GAMax.Individual.setDefaultGeneLength(int.Parse(BinaryLengthTextBox.Text));
GSA.GAMax.Population maxPop = new GSA.GAMax.Population(int.Parse(PopulationNumberTextBox.Text), true);
GSA.GAMax.FitnessCalc._op = (GSA.GAMax.Operation)maxOrMin;
if (GSA.GAMax.FitnessCalc.setFunctionToOperate(FormulaTextBox.Text)) {
log.Write(String.Format("Function setted: {0}", GSA.GAMax.FitnessCalc._exp.ParsedExpression.ToString()), Brushes.Azure);
//setear población
log.Write("Initial population, size: " + maxPop.size().ToString(), Brushes.Turquoise);
for (int i = 0; i < maxPop.size(); i++) {
log.Write(maxPop.getIndividual(i).ToString(), Brushes.Wheat);
}
} else {
log.Write(String.Format("Your function has errors: {0}", GSA.GAMax.FitnessCalc._exp.Error), Brushes.PaleVioletRed);
log.Write("The function must be correct and contains an 'x' between []. Example 'Pow([x], 3) + 5*[x] - 2 / ([x]+2)", Brushes.PaleVioletRed);
}
int generationCount = 0;
int MaxGeneration = int.Parse(MaxIterationsTextBox.Text);
while (generationCount < MaxGeneration) {
generationCount++;
//log.Write("Generation: " + generationCount + " Fittest: " + myPop.getFittest().getFitness(), Brushes.Yellow);
GSA.GAMax.FitnessCalc.CurrentPopulation = maxPop;
maxPop = GSA.GAMax.Algorithm.evolvePopulation(maxPop);
}
log.Write("Best Solution found!", Brushes.GreenYellow);
log.Write("Generation: " + generationCount);
log.Write("Genes:");
GSA.GAMax.Individual bestSolutionFound = GSA.GAMax.FitnessCalc.getFittest();
if (!GSA.GAMax.Algorithm.betterFitness(GSA.GAMax.Algorithm.bestSolution, bestSolutionFound)) {
bestSolutionFound = GSA.GAMax.Algorithm.bestSolution;
}
log.Write(bestSolutionFound.ToString());
}