public void RunGDE3 <S>()
where S : ContinuousVector, new()
{
GDE3 <S> algorithm = new GDE3 <S>(GetProblem());
algorithm.PopulationSize = 100;
algorithm.Initialize();
ClearStatusInfo();
BackgroundWorker worker = new BackgroundWorker();
worker.WorkerReportsProgress = true;
worker.DoWork += (s1, e1) =>
{
while (!algorithm.IsTerminated)
{
algorithm.Evolve();
worker.ReportProgress(0);
}
};
worker.ProgressChanged += (s1, e1) =>
{
txtStatus1.Text = string.Format("Current Generation: {0}", algorithm.CurrentGeneration);
txtStatus2.Text = string.Format("Size of Archive: {0}", algorithm.NondominatedArchiveSize);
};
worker.RunWorkerCompleted += (s1, e1) =>
{
NondominatedPopulation <S> archive = algorithm.NondominatedArchive;
DisplayParetoFront(archive);
};
worker.RunWorkerAsync();
}
private void DisplayParetoFront <S>(NondominatedPopulation <S> archive)
where S : ContinuousVector, new()
{
GraphPane pane = chtParetoFront.GraphPane;
pane.XAxis.Title.Text = "Objective 1";
pane.YAxis.Title.Text = "Objective 2";
pane.Title.Text = string.Format("Problem: {0}", (ProblemType)cboProblem.SelectedItem);
PointPairList list = new PointPairList();
foreach (S s in archive.Solutions)
{
list.Add(s.FindObjectiveAt(0), s.FindObjectiveAt(1));
}
AlgorithmType algorithm_type = (AlgorithmType)cboAlgorithm.SelectedItem;
LineItem myCurve = pane.AddCurve(string.Format("{0} ({1})", algorithm_type.ToString(), cboProblem.SelectedItem), list, GetParetoFrontColor());
myCurve.Symbol.Type = ZedGraph.SymbolType.Plus;
myCurve.Line.IsVisible = false;
pane.AxisChange();
chtParetoFront.Invalidate();
DataTable table = new DataTable();
table.Columns.Add("#");
IMOOProblem problem = archive[0].Problem;
for (int i = 0; i < problem.GetObjectiveCount(); ++i)
{
table.Columns.Add(string.Format("Objective {0}", i + 1));
}
for (int i = 0; i < problem.GetDimensionCount(); ++i)
{
table.Columns.Add(string.Format("x[{0}]", i));
}
for (int i = 0; i < archive.Count; ++i)
{
S s = archive[i];
List <object> values = new List <object>();
values.Add(i + 1);
for (int j = 0; j < problem.GetObjectiveCount(); ++j)
{
values.Add(s.FindObjectiveAt(j));
}
for (int j = 0; j < problem.GetDimensionCount(); ++j)
{
values.Add(s[j]);
}
table.Rows.Add(values.ToArray());
}
dgvParetoFront.DataSource = table;
}
static void RunHybridGame()
{
HybridGame <ContinuousVector> algorithm = new HybridGame <ContinuousVector>(new NDNDProblem());
algorithm.Config.PopulationSize = 100;
algorithm.Initialize();
while (!algorithm.IsTerminated)
{
algorithm.Evolve();
Console.WriteLine("Current Generation: {0}", algorithm.CurrentGeneration);
Console.WriteLine("Size of Archive: {0}", algorithm.NondominatedArchiveSize);
}
NondominatedPopulation <ContinuousVector> paretoFront = algorithm.NondominatedArchive;
}
public static void Main(string[] args)
{
#region variables
int nPopulation = 100;
//string fragmentsDefinitionPath = "Fragments.txt";
//Dictionary<int, IFragmentElemet> VectorTemplate = new Dictionary<int, IFragmentElemet>(); //string shows fragmentElement and int shows its location in population
//Dictionary<int, Dictionary<int, IFragmentElemet>> ModelFragmentVector = new Dictionary<int, Dictionary<int, IFragmentElemet>>(); //string shows fragmentElement and int shows its location in population
Dictionary <Model, int> ModelFragmentVector = new Dictionary <Model, int>();
//List<int[]> population = new List<int[]>(); //each bool shows if a fragment is selected or not
List <Dictionary <Model, int> > population = new List <Dictionary <Model, int> >();
System.Random rnd = new System.Random();
#endregion
#region work with model
var repository = new ModelRepository();
//var model = repository.Resolve("ClassModel.xmi");
//var model_a = repository.Resolve("a.xmi");
//var classModel_a = model_a.RootElements[0] as ClassModel;
var model_b = repository.Resolve("b.xmi");
var classModel_b = model_b.RootElements[0] as ClassModel;
//var model_c = repository.Resolve("c.xmi");
//var classModel_c = model_c.RootElements[0] as ClassModel;
//var model_d = repository.Resolve("d.xmi");
//var classModel_d = model_d.RootElements[0] as ClassModel;
//var model_e = repository.Resolve("e.xmi");
//var classModel_e = model_e.RootElements[0] as ClassModel;
//step 1: Read All Fragments
DirectoryInfo d = new DirectoryInfo("Inputs");//Assuming Test is your Folder
FileInfo[] Files = d.GetFiles("*.xmi");
foreach (FileInfo file in Files)
{
//step2:Make solution space based on loaded Fragments
try
{
var fragmentModel = repository.Resolve(file.FullName);
var fragmentClassModel = fragmentModel.RootElements[0] as ClassModel; // for trace purpose only
ModelFragmentVector.Add(fragmentModel, 0); //temp
}
catch (Exception ex)
{ }
}
//step2:Make solution space based on loaded Fragments
for (int i = 0; i < nPopulation; i++)
{
//int[] solution = new int[ModelFragmentVector.Count];
//for (int j = 0; j < ModelFragmentVector.Count; j++)
// solution[j] = rnd.NextDouble() >= 0.5 ? 1 : 0;
//population.Add(solution);
//clone as ModelFragmentVector
Dictionary <Model, int> solution = new Dictionary <Model, int>();
foreach (KeyValuePair <Model, int> entry in ModelFragmentVector)
{
solution.Add(entry.Key, rnd.NextDouble() >= 0.5 ? 1 : 0);
}
//add to population
population.Add(solution);
}
//step3: write objectives
//step4: run the algorithm
#endregion work with model
#region work with meta-model
#region create vector template
//Type[] typelist = GetTypesInNamespace(Assembly.GetExecutingAssembly(), "MDEMGTT.ArchitectureCRA");
//for (int i = 0; i < typelist.Length; i++)
// if (!typelist[i].GetTypeInfo().IsInterface)
// VectorTemplate.Add(typelist[i].Name, false);
#endregion make solution space from template
#endregion work with meta-model
Console.WriteLine("Model Fragments Extracted!");
#region algrorithm play
//NSGAII<ContinuousVector> algorithm = new NSGAII<ContinuousVector>(new CRAProblem(population, ModelFragmentVector));
Algorithms.NSGAII algorithm = new Algorithms.NSGAII(new CRAProblem(population, ModelFragmentVector));
algorithm.PopulationSize = 100;
algorithm.Initialize();
while (!algorithm.IsTerminated)
{
algorithm.Evolve();
Console.WriteLine("Current Generation: {0}", algorithm.CurrentGeneration);
Console.WriteLine("Size of Archive: {0}", algorithm.NondominatedArchiveSize);
}
ContinuousVector finalSolution = algorithm.GlobalBestSolution;
NondominatedPopulation <ContinuousVector> paretoFront = algorithm.NondominatedArchive;
Console.WriteLine(finalSolution.CrowdingDistance);
Console.WriteLine(paretoFront.Count);
Console.ReadKey();
#endregion algorithm play
}
