public void CombinedPopulationCount()
{
int pop = 10;
Population p1 = new Population();
p1.NewPopulation(pop);
Population p2 = new Population();
p2.NewPopulation(pop);
Population p3 = p1.Concat(p2);
Assert.AreEqual(p3.GetCount(), p1.GetCount() + p2.GetCount());
}
public void InitialPopulationBoundaries()
{
Algorithm nsga = new Nsga2();
int pop = 10;
TestFunctions funcs = TestFunctions.GetTestFunctions();
Population p = new Population();
p.NewPopulation(pop);
int mistakes = 0;
for (int i = 0; i < p.GetCount(); i++)
{
for (int j = 0; j < p.Get(i).DecisionVariables.Count; j++)
{
if (p.Get(i).DecisionVariables[0] < funcs.GetLowerThreshold()
|| p.Get(i).DecisionVariables[j] > funcs.GetUpperThreshold())
{
mistakes++;
}
}
}
Assert.AreEqual(mistakes, 0);
}
public void CrossoverTest()
{
GeneticOperators operators = new GeneticOperators();
int pop = 10;
Population genom = new Population();
genom.NewPopulation(pop);
List<Solution> newGenom = new List<Solution>();
for (int i = 0; i < genom.GetCount() - 1; i += 2)
{
List<Solution> list = operators.Crossover(genom.Get(i), genom.Get(i + 1));
foreach (Solution s in list)
{
newGenom.Add(s);
}
}
if (newGenom.Count < genom.GetCount())
{
newGenom.Add(genom.Get(genom.GetCount()-1));
}
double eps = 0.001;
int mistakes = 0;
List<Solution>.Enumerator e = newGenom.GetEnumerator();
int j = -1;
while (e.MoveNext())
{
j++;
for (int i = 0; i < e.Current.DecisionVariables.Count; i++)
{
if (Math.Abs(e.Current.DecisionVariables[i] - genom.Get(j).DecisionVariables[i]) < eps)
{
mistakes++;
}
}
}
Assert.AreEqual(0, mistakes);
}
public void SelectionCountTest()
{
int pop = 10;
Population genom = new Population();
genom.NewPopulation(pop);
Population genom2 = new Population();
genom2.NewPopulation(pop);
Population combined = genom.Concat(genom2);
genom = combined.Selection();
Assert.AreEqual(combined.GetCount() / 2, genom.GetCount());
}
public Population StartEvaluation(int populationCount, int generationCount)
{
infinite = 10000;
Population genom = new Population();
genom.NewPopulation(populationCount);
Console.WriteLine("Initial population");
genom.PrintToConsole();
Population newGenom = genom.CreateOffspring();
Console.WriteLine("Initial population after creating offspring pop");
genom.PrintToConsole();
Console.WriteLine("Offspring population");
newGenom.PrintToConsole();
FastNonDominatedSort(genom);
RankingsPrintToConsole();
for (int i = 0; i < generationCount; i++)
{
Population combinedGenom = genom.Concat(newGenom);
FastNonDominatedSort(combinedGenom);
genom.RemoveAll();
AssignCrowdingDistance();
genom.Copy(SortPopulation(combinedGenom).Selection());
newGenom = genom.CreateOffspring();
}
newGenom.PrintToConsole();
this.RankingsPrintToConsole();
//PrintToConsole(genom);
// genom.PrintToConsole();
return genom;
}
