/// <summary>
/// Wznawianie Algorytmu Genetycznego
/// </summary>
private void ResumeGA()
{
RunGA(() =>
{
m_ga.Population.MinSize = Convert.ToInt32(PopulationMinUpDown.Value);
m_ga.Population.MaxSize = Convert.ToInt32(PopulationMaxUpDown.Value);
m_ga.Selection = m_selection;
m_ga.Crossover = m_crossover;
m_ga.Mutation = m_mutation;
float[] globalmin = new float[testnumber];
double wynik = 0;
double bestresult = 0;
double worstresult = 0;
double percentsucess = 0;
double tmpbest = 0;
double tmpworst = 0;
//m_ga.CrossoverProbability = Convert.ToSingle(hslCrossoverProbability.Value);
m_ga.MutationProbability = Convert.ToSingle(MutationProbTrackbar.Value);
m_ga.Reinsertion = m_reinsertion;
m_ga.Termination = m_termination;
richTextAlGenet.AppendText("Średnie wartości funkci: " + wynik / testnumber + "\n" + "\n");
richTextAlGenet.AppendText("Najlepsza wartość funkcji: " + bestresult + "\n" + "\n");
richTextAlGenet.AppendText("Najgorsza wartość funkcji: " + worstresult + "\n" + "\n");
richTextAlGenet.AppendText("Procent sukcesu: " + percentsucess / testnumber * 100 + "%" + "\n" + "\n");
m_ga.Resume();
});
}
