private void Button_Click(object sender, RoutedEventArgs e)
{
InputGraph data = new InputGraph();
data = ReadData();
Optimization(data);
DrawGraph();
}
private InputGraph ReadData()
{
InputGraph _data = new InputGraph();
double _generations, _population, _crossoverProb, _mutationProb;
double _featureAMax, _featureBMax, _featureCMax, _featureDMax;
double _featureAMin, _featureBMin, _featureCMin, _featureDMin;
double.TryParse(this.TextBoxGeneration.Text, out _generations);
_data.generations = _generations;
double.TryParse(this.TextBoxPopulation.Text, out _population);
_data.population = _population;
double.TryParse(this.TextBoxCrossover.Text, out _crossoverProb);
_data.crossoverProb = _crossoverProb;
double.TryParse(this.TextBoxMutation.Text, out _mutationProb);
_data.mutationProb = _mutationProb;
double.TryParse(this.TextBoxAMin.Text, out _featureAMin);
_data.featureAMin = _featureAMin;
double.TryParse(this.TextBoxAMax.Text, out _featureAMax);
_data.featureAMax = _featureAMax;
double.TryParse(this.TextBoxBMin.Text, out _featureBMin);
_data.featureBMin = _featureBMin;
double.TryParse(this.TextBoxBMax.Text, out _featureBMax);
_data.featureBMax = _featureBMax;
double.TryParse(this.TextBoxCMin.Text, out _featureCMin);
_data.featureCMin = _featureCMin;
double.TryParse(this.TextBoxCMax.Text, out _featureCMax);
_data.featureCMax = _featureCMax;
double.TryParse(this.TextBoxDMin.Text, out _featureDMin);
_data.featureDMin = _featureDMin;
double.TryParse(this.TextBoxDMax.Text, out _featureDMax);
_data.featureDMax = _featureDMax;
return(_data);
}
public Results Optimization(InputGraph _data)
{
//double[,] rangeFeatures = new double[,] { { 10, 15 }, { 10, 15 }, { 8, 15 }, { 0.005, 1 } };
double[,] rangeFeatures = new double[, ] {
{ _data.featureAMin, _data.featureAMax },
{ _data.featureBMin, _data.featureBMax },
{ _data.featureCMin, _data.featureCMax },
{ _data.featureDMin, _data.featureDMax }
};
double[] rangeMeasurement = new double[100];
double aux = 0;
for (int i = 0; i < rangeMeasurement.Length; i++)
{
rangeMeasurement[i] = aux + 0.1;
aux = rangeMeasurement[i];
}
Function evalTarget = new Function(rangeMeasurement);
double[,] result = evalTarget.Evaluation(new double[] { 12, 12, 10.5, 0.01 });
////Population, rangeFeatures, result, rangeMeasuremet
//GA_1 = new GeneticAlgorithm(100, rangeFeatures, result, rangeMeasurement);
////Generation, Pcrossover, Pmutation
//GA_1.Run(300, 0.9, 0.1);
double[] xVar = rangeMeasurement;
double[] yVar = new double[rangeMeasurement.Length];
for (int i = 0; i < rangeMeasurement.Length; i++)
{
yVar[i] = result[i, 1];
}
//Population, rangeFeatures, xVat, YVar
//GA_1 = new GeneticAlgorithm(1000, rangeFeatures, xVar, yVar);
GA = new GeneticAlgorithm((int)_data.population, rangeFeatures, xVar, yVar);
//Generation, Pcrossover, Pmutation
//GA_1.Run(500, 0.9, 0.9);
GA.Run(_data.generations, _data.crossoverProb, _data.mutationProb);
return(GA.results);
}