private Reduct ChooseNextNeighbor(IEnumerable <Reduct> neighborsList, out int?indexOfIndividualChange)
{
Reduct bestNeighbor = null;
indexOfIndividualChange = null;
foreach (var neighbor in neighborsList)
{
var index = GetIndexOfIndividualStringChange(neighbor);
if (index == null)
{
continue;
}
// ReSharper disable once InvertIf
if ((ShouldChangeBestSolution(neighbor) || _tabuList[(int)index] == 0))
// &&
//(neighbor.Approximation >= 0.9 * AllAttributesSolution.Approximation || neighbor.FitnessFunction <= BestSolution.FitnessFunction)
{
bestNeighbor = neighbor;
indexOfIndividualChange = index;
break;
}
}
return(bestNeighbor);
}
private void SetInitialSolution()
{
var individual = BinaryStringHelper.GenerateRandomIndividual(IndividualLength);
ActualSolution = new Reduct(individual, ClusteredDataObjects);
CheckedReducts.Add(ActualSolution);
}
public override void Calculate()
{
CalculateApproximationForAllAttributes();
SetInitialSolution();
BestSolution = ActualSolution;
while (++IterationWithoutImprovementCount != _inputValues.IterationWithoutImprovement)
{
++IterationNumber;
var neighborsList = GenerateSortedNeighborhoodForActualSolution();
int?indexOfIndividualChange;
var bestNeighbor = ChooseNextNeighbor(neighborsList, out indexOfIndividualChange);
if (indexOfIndividualChange == null)
{
continue;
}
ActualSolution = bestNeighbor;
TabuListActualization((int)indexOfIndividualChange);
TryToUpdateBestSolution(ActualSolution);
AddToIterationResultsList(BestSolution.FitnessFunction, BestSolution.Approximation, BestSolution.Subset.Count);
}
}
private Reduct MutateIndividual(Reduct reduct)
{
var individual = reduct.Individual;
var mutationIndex = RandomIntNumber(IndividualLength);
var newGeneValue = individual[mutationIndex] == '1' ? '0' : '1';
var newIndividual = individual.Substring(0, mutationIndex) + newGeneValue + individual.Substring(mutationIndex + 1);
return(new Reduct(newIndividual, ClusteredDataObjects));
}
protected void TryToUpdateBestSolution(Reduct reduct)
{
if (!ShouldChangeBestSolution(reduct))
{
return;
}
BestSolution = reduct;
IterationWithoutImprovementCount = 0;
}
private int?GetIndexOfIndividualStringChange(Reduct bestNeighbor)
{
for (var i = 0; i < IndividualLength; i++)
{
if (ActualSolution == null || bestNeighbor == null || ActualSolution.Individual[i] == bestNeighbor.Individual[i])
{
continue;
}
return(i);
}
return(null);
}
public override void Calculate()
{
CalculateApproximationForAllAttributes();
for (var i = 1; i < _numberOfSolutions; i++)
{
var individual = BinaryStringHelper.ConvertIntToBinaryString(i, IndividualLength);
var reduct = new Reduct(individual, ClusteredDataObjects);
if (ShouldChangeBestSolution(reduct))
{
BestSolution = reduct;
}
}
}
private void GenerateNewSolutionFromNeighbors(Reduct eliteReduct, int neighborhoodSize, int neighborhoodSteps)
{
var neighborhood = new List <Reduct>();
for (var i = 0; i < neighborhoodSize; i++)
{
var neighborIndividual = string.Empty;
for (var j = 0; j < neighborhoodSteps; j++)
{
neighborIndividual = BinaryStringHelper.GenerateNeighborSolution(eliteReduct.Individual);
}
TryAddReductToCheckedReductsList(neighborIndividual);
neighborhood.Add(CheckedReducts.FirstOrDefault(r => r.Individual == neighborIndividual));
}
ActualPopulation.Individuals.Add(neighborhood.OrderByDescending(r => r.Approximation).ThenBy(i => i.Subset.Count).FirstOrDefault());
}
protected bool ShouldChangeBestSolution(Reduct reduct)
{
bool shouldChangeBestSolution;
if (reduct == null)
{
shouldChangeBestSolution = false;
}
else if (BestSolution == null)
{
shouldChangeBestSolution = true;
}
else
{
shouldChangeBestSolution = (reduct.FitnessFunction < BestSolution.FitnessFunction || (reduct.FitnessFunction == BestSolution.FitnessFunction && reduct.Subset.Count < BestSolution.Subset.Count))
&&
(reduct.Approximation > 0.9 * AllAttributesSolution.Approximation || reduct.Approximation >= BestSolution.Approximation);
}
return(shouldChangeBestSolution);
}
private void CreateNewReduct(string individual)
{
var reduct = new Reduct(individual, ClusteredDataObjects);
CheckedReducts.Add(reduct);
}
protected void CalculateApproximationForAllAttributes()
{
var individual = BinaryStringHelper.GenerateIndividualWithAllAttributes(IndividualLength);
AllAttributesSolution = new Reduct(individual, ClusteredDataObjects);
}
