public Generation(IEnumerable<Chromosome> chromosomes, AlgorithmSettings settings)
{
Id = 0;
InitialChromosomes = chromosomes.ToList();
Settings = settings;
Previous = null;
}
private void button1_Click(object sender, EventArgs e)
{
richTextBox1.Text = "";
desc.Clear();
alg = new PGA();
OptimizationModel optModel = new OptimizationModel(func);
AlgorithmSettings settings = new AlgorithmSettings()
{
InitialLoadType = (InitialLoadType)comboBox1.SelectedItem,
OptModel = optModel,
InitialPointCount = (int)numericUpDown1.Value,
SelectionType = (SelectionType)comboBox2.SelectedItem,
EndCondition = (EndCondition)comboBox3.SelectedItem,
MaxGenerationCount = (int)numericUpDown2.Value,
SurvivedCount = (int)numericUpDown3.Value,
MutationChance = (double)numericUpDown4.Value,
CrossingGenNumber = (int)numericUpDown5.Value,
Tolerance = (double)numericUpDown6.Value,
MutationChanceAfterCrossing = (double)numericUpDown7.Value,
MutationType = (MutationType)comboBox4.SelectedItem
};
alg.Run(settings);
DrawRezult(alg);
WriteRezult(alg);
}
public void Run(AlgorithmSettings settings)
{
settings.OptModel.ResetCallCount();
Chromosome.ResetIdentity();
InitialMesh = MeshService.GetMesh(settings.OptModel, settings.InitialPointCount, settings.InitialLoadType);
Generations = new List<Generation>();
Generations.Add(new Generation(InitialMesh.Chromosomes, settings));
int i = 0;
while (!Generations[i].IsFinal)
{
Generations.Add(new Generation(Generations[i]));
i++;
}
CallCount = settings.OptModel.CallCount;
Best = Generations[i].BestChromosome;
}
private void backgroundWorker1_DoWork(object sender, DoWorkEventArgs e)
{
int progress = 0;
optrez.Clear();
finalRez.Clear();
alg = new PGA();
OptimizationModel optModel = new OptimizationModel(func);
EnumConverter InitialLoadTypeCollection = new EnumConverter(typeof(InitialLoadType));
EnumConverter EndConditionTypeCollecton = new EnumConverter(typeof(EndCondition));
EnumConverter MutationTypeCollecton = new EnumConverter(typeof(MutationType));
EnumConverter SelectionTypeCollection = new EnumConverter(typeof(SelectionType));
foreach (InitialLoadType il in InitialLoadTypeCollection.GetStandardValues())
{
foreach (EndCondition ec in EndConditionTypeCollecton.GetStandardValues())
{
foreach (MutationType mt in MutationTypeCollecton.GetStandardValues())
{
foreach (SelectionType st in SelectionTypeCollection.GetStandardValues())
{
double[] f1m = new double[(int)numericUpDown8.Value];
double[] f2m = new double[(int)numericUpDown8.Value];
double[] fm = new double[(int)numericUpDown8.Value];
double[] x1m = new double[(int)numericUpDown8.Value];
double[] x2m = new double[(int)numericUpDown8.Value];
for (int i = 0; i < (int)numericUpDown8.Value; i++)
{
AlgorithmSettings settings = new AlgorithmSettings()
{
InitialLoadType = il,
OptModel = optModel,
InitialPointCount = (int)numericUpDown1.Value,
SelectionType = st,
EndCondition = ec,
MaxGenerationCount = (int)numericUpDown2.Value,
SurvivedCount = (int)numericUpDown3.Value,
MutationChance = (double)numericUpDown4.Value,
CrossingGenNumber = (int)numericUpDown5.Value,
Tolerance = (double)numericUpDown6.Value,
MutationChanceAfterCrossing = (double)numericUpDown7.Value,
MutationType = mt
};
alg.Run(settings);
double x1 = alg.Best.X1;
double x2 = alg.Best.X2;
double f1 = alg.Best.F;
double f2 = alg.CallCount;
double f = GetCriterion(f1, f2);
f1m[i] = f1;
f2m[i] = f2;
fm[i] = f;
x1m[i] = x1;
x2m[i] = x2;
optrez.Add(new OptRezult()
{
I = il,
E = ec,
S = st,
M = mt,
F1 = f1,
F2 = f2,
X1 = x1,
X2 = x2,
F = f
});
}
progress++;
backgroundWorker1.ReportProgress(progress * 100 / 24);
finalRez.Add(new OptRezult()
{
I = il,
E = ec,
S = st,
M = mt,
X1 = x1m.Average(),
X2 = x2m.Average(),
F1 = f1m.Average(),
F2 = f2m.Average(),
F = fm.Average()
});
}
}
}
}
}
