public void RandomInitialize()
{
// Generate Initial Population
for (int idx = 0; idx < this.InitialPopulationSize; ++idx)
{
IndividualBase individual = problem.CreateRandomSolution();
IndividualEvaluator.Execute(individual, problem);
AddIndividual(individual);
}
}
protected override void EvaluateObjectiveValues()
{
// Create Temporary Individuals
List <IndividualBase> temporaryList = new List <IndividualBase>();
for (int iCount = 0; iCount < 200; ++iCount)
{
IndividualBase i = Problem.CreateRandomSolution();
IndividualEvaluator.Execute(i, Problem);
temporaryList.Add(i);
}
double maxValueFound = temporaryList.Max(I => I.GetFitnessForObjective(Problem.MonoObjectiveGoal));
double adaptedMaxValue = Math.Abs(maxValueFound) * 2;
Problem.MonoObjectiveGoal.BigValueForMaximization = adaptedMaxValue;
}
private Population_MonoObjective_AG RunGeneration(Population_MonoObjective_AG currentGeneration, SelectionMethodBase selectionMethod, CrossoverMethodBase crossoverMethod, /*IReinsertionMethod reinsertionMethod, */ ReinsertionMethodBase reinsertionMethod)
{
Population_MonoObjective_AG recentlyBorn = new Population_MonoObjective_AG(Problem, InitialPopulationSize);
int expectedChildCount = ((InitialPopulationSize * reinsertionMethod.OffspringPercentage) / 100);
while (recentlyBorn.IndividualCount < expectedChildCount)
{
IndividualBase parent1 = null, parent2 = null, child1 = null, child2 = null;
selectionMethod.Execute(currentGeneration, out parent1, out parent2);
crossoverMethod.Execute(parent1, parent2, out child1, out child2);
recentlyBorn.AddIndividual(child1);
recentlyBorn.AddIndividual(child2);
}
int mutatedChildCount = ((recentlyBorn.IndividualCount * mutationPct) / 100);
for (int idx = 0; idx < mutatedChildCount; ++idx)
{
IndividualBase randomIndividual = recentlyBorn.GetRandomIndividual();
Problem.MutateIndividual(randomIndividual);
}
IndividualBase individual = null;
for (int idx = 0; idx < recentlyBorn.IndividualCount; ++idx)
{
individual = recentlyBorn.Content[idx];
Problem.ValidateIndividual(individual);
IndividualEvaluator.Execute(individual, Problem);
}
Population_MonoObjective_AG newGeneration = reinsertionMethod.Execute(currentGeneration, recentlyBorn);
return(newGeneration);
}