public void OffspringPopulationBoundaries()
{
Algorithm nsga = new Nsga2();
int pop = 10;
TestFunctions funcs = TestFunctions.GetTestFunctions();
Population parent = new Population();
parent.NewPopulation(pop);
Population p = parent.CreateOffspring();
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 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;
}