public static Report Calculate(
int n, List <int> a, List <int> b, int B,
SelectionType selectionType, LocalOptimization optimization,
int numberOfIterations = 10, int populationSize = 15)
{
if (numberOfIterations < 3)
{
numberOfIterations = 3;
}
NumberOfGenes = populationSize;
RecordsForMax = new List <int>();
int iterationsForMax = 0, recordForMax = int.MinValue;
CreatePopulation(n, a, b, B);
do
{
switch (selectionType)
{
case SelectionType.Tournament: MakeTournamentSelectionForMax();
break;
case SelectionType.FullyRandom: MakeFullyRandomSelection();
break;
case SelectionType.PartlyRandom: MakeSelectionWithMaxAndRandom();
break;
case SelectionType.OutBreeding: MakeOutBreedingSelection();
break;
}
FirstChild = Gene.Recombinate(FirstParent.Chromosomes, SecondParent.Chromosomes, n);
SecondChild = Gene.Recombinate(FirstParent.Chromosomes, SecondParent.Chromosomes, n);
FirstChild.Mutate(a, b);
SecondChild.Mutate(a, b);
FirstChild.Reanimate(a, b, B);
SecondChild.Reanimate(a, b, B);
switch (optimization)
{
case LocalOptimization.Optimize:
FirstChild.OptimizeForMax(a, b, B);
SecondChild.OptimizeForMax(a, b, B);
break;
}
UpdatePopulationForMax();
if (recordForMax < Population[GetIndexOfMaxGen()].Fitness)
{
recordForMax = Population[GetIndexOfMaxGen()].Fitness;
}
RecordsForMax.Add(recordForMax);
} while (!isReadyToStop(RecordsForMax, ++iterationsForMax, numberOfIterations));
CreatePopulation(n, a, b, B);
RecordsForMin = new List <int>();
int recordForMin = int.MaxValue, iterationsForMin = 0;
do
{
switch (selectionType)
{
case SelectionType.Tournament: MakeTournamentSelectionForMin();
break;
case SelectionType.FullyRandom: MakeFullyRandomSelection();
break;
case SelectionType.PartlyRandom: MakeSelectionWithMinAndRandom();
break;
case SelectionType.OutBreeding: MakeOutBreedingSelection();
break;
}
FirstChild = Gene.Recombinate(FirstParent.Chromosomes, SecondParent.Chromosomes, n);
SecondChild = Gene.Recombinate(FirstParent.Chromosomes, SecondParent.Chromosomes, n);
FirstChild.Mutate(a, b);
SecondChild.Mutate(a, b);
FirstChild.Reanimate(a, b, B);
SecondChild.Reanimate(a, b, B);
switch (optimization)
{
case LocalOptimization.Optimize:
FirstChild.OptimizeForMin(a, b, B);
SecondChild.OptimizeForMin(a, b, B);
break;
}
UpdatePopulationForMin();
if (recordForMin > Population[GetIndexOfMinGen()].Fitness)
{
recordForMin = Population[GetIndexOfMinGen()].Fitness;
}
RecordsForMin.Add(recordForMin);
} while (!isReadyToStop(RecordsForMin, ++iterationsForMin, numberOfIterations));
return(new Report(
(recordForMax, iterationsForMax, RecordsForMax),
(recordForMin, iterationsForMin, RecordsForMin)));
}
