public virtual void Copy(MOOSolution rhs)
{
mObjectives.Clear();
mConstaints.Clear();
int objective_count = rhs.mObjectives.Count;
for (int objective_index = 0; objective_index < objective_count; ++objective_index)
{
mObjectives.Add(rhs.mObjectives[objective_index]);
}
int constraint_count = rhs.mConstaints.Count;
for (int constraint_index = 0; constraint_index < constraint_count; ++constraint_index)
{
mConstaints.Add(rhs.mConstaints[constraint_index]);
}
mTags.Clear();
Dictionary <string, object> tags = rhs.mTags;
foreach (string tag_id in tags.Keys)
{
mTags[tag_id] = tags[tag_id];
}
mRank = rhs.mRank;
mCrowdingDistance = rhs.mCrowdingDistance;
mPopulation = rhs.mPopulation;
mProblem = rhs.mProblem;
}
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;
}
public HybridGame(IMOOProblem problem)
{
mProblem = problem;
int dimension_count = problem.GetDimensionCount();
for (int i = 0; i < dimension_count; ++i)
{
mEliteDesignVariables[i] = 0;
}
}
public override List <S> Crossover(P pop, params S[] parents)
{
List <S> results = new List <S>();
int dimension_count = pop.Problem.GetDimensionCount();
IMOOProblem problem = pop.Problem;
double crossover_rate = pop.CrossoverRate;
int ccount = parents.Length;
S child1, parent1, parent2, parent3;
for (int i = 0; i < ccount; i += 4)
{
int child1_index = i;
int parent1_index = (i + 1) % ccount;
int parent2_index = (i + 2) % ccount;
int parent3_index = (i + 3) % ccount;
child1 = parents[child1_index].Clone() as S;
parent1 = parents[parent1_index];
parent2 = parents[parent2_index];
parent3 = parents[parent3_index];
int jrand = DistributionModel.NextInt(dimension_count);
for (int j = 0; j < dimension_count; j++)
{
if ((DistributionModel.GetUniform() <= crossover_rate) || (j == jrand))
{
double v1 = parent1[j];
double v2 = parent2[j];
double v3 = parent3[j];
double y = v3 + mF * (v1 - v2);
if (y < problem.GetLowerBound(j))
{
y = problem.GetLowerBound(j);
}
if (y > problem.GetUpperBound(j))
{
y = problem.GetUpperBound(j);
}
child1[j] = y;
}
}
results.Add(child1);
}
return(results);
}
public NashNode(IMOOProblem problem, MOOConfig config, Dictionary <int, double> elite_design_variables, Dictionary <int, int> design_variable_local_mapping, int objective_index)
{
mGlobalEliteDesignVariables = elite_design_variables;
mDesignVariableGlobal2LocalMapping = design_variable_local_mapping;
foreach (int design_variable_global_index in design_variable_local_mapping.Keys)
{
mLocalEliteDesignVariables[design_variable_global_index] = -1;
mDesignVariableLocal2GlobalMapping[design_variable_local_mapping[design_variable_global_index]] = design_variable_global_index;
}
mOriginalProblem = problem;
mObjectiveIndex = objective_index;
mPopulation = CreatePopulation();
mPopulation.Problem = this;
mPopulation.Config.Copy(config);
mMutationInstructionFactory = CreateMutationInstructionFactory();
mCrossoverInstructionFactory = CreateCrossoverInstructionFactory();
mPopInitInstructionFactory = CreatePopInitInstructionFactory();
mReproductionSelectionInstructionFactory = CreateSelectionInstructionFactory();
}
public NSGAII(IMOOProblem problem)
: base(problem)
{
}
public ContinuousVector(IMOOPop pop, IMOOProblem problem)
: base(pop, problem)
{
}
public MOOSolution(IMOOPop population, IMOOProblem problem)
{
mPopulation = population;
mProblem = problem;
}
public GDE3(IMOOProblem problem)
: base(problem)
{
}
public ParetoNode(IMOOProblem problem)
: base(problem)
{
}
public HAPMOEA(IMOOProblem problem1, IMOOProblem problem2, IMOOProblem problem3)
{
mProblem1 = problem1;
mProblem2 = problem2;
mProblem3 = problem3;
}
public HAPMOEA(IMOOProblem problem)
{
mProblem1 = problem;
mProblem2 = problem;
mProblem3 = problem;
}
public HAPMOEALayer(IMOOProblem problem, HAPMOEAConfig config)
{
mProblem = problem;
mConfig = config;
}
