public KrillHerdAlgorithm(KrillPopulation krillPopulation, FitnessFunction fitnessFunctionDelegate, Vector <double> LB_vector, Vector <double> UB_vector)
{
this.LB_vector = LB_vector;
this.UB_vector = UB_vector;
KrillPopulation = krillPopulation;
FitnessFunction = fitnessFunctionDelegate;
}
public VirtualFood(KrillPopulation krillPopulation, FitnessFunction fitnessFunction, Vector <double> UB_Vector, Vector <double> LB_Vector)
{
this.UB_Vector = UB_Vector;
this.LB_Vector = LB_Vector;
KrillPopulation = krillPopulation;
FitnessFunction = fitnessFunction;
PositionOfFood = Vector <double> .Build.Dense(krillPopulation.Population[0].Coordinates.Count);
}
void Krill_OnGenerationComplete(object sender, RunEventArgs e)
{
KrillPopulation population = (KrillPopulation)sender;
var bestKrill = population.GetBestKrill();
Console.WriteLine("Iteration: {0}, Fitness: {1}, Coordinates: ({2}, {3})",
e.Iteration, Math.Round(bestKrill.Fitness, 4), Math.Round(bestKrill.Coordinates[0], 4), Math.Round(bestKrill.Coordinates[1], 4));
}
public InducedMotion(KrillPopulation KrillPopulation, FitnessFunction fitnessFunction, int maxIteration, double N_max)
: base(KrillPopulation, fitnessFunction)
{
this.KrillPopulation = KrillPopulation;
Neighbourhood = new Neighbourhood(this.KrillPopulation);
InducedSpeedHistory = new Dictionary <Tuple <int, int>, Vector <double> >();
MaxIteration = maxIteration;
this.N_max = N_max;
}
public ForagingMotion(KrillPopulation KrillPopulation, FitnessFunction fitnessFunction, int maxIteration, double V_f)
: base(KrillPopulation, fitnessFunction)
{
F_i_old = Vector <double> .Build.Dense(KrillPopulation.Population[0].Coordinates.Count);
this.V_f = V_f;
MaxIteration = maxIteration;
ForagingSpeedHistory = new Dictionary <Tuple <int, int>, Vector <double> >();
}
private void PopulationInitialization()
{
// Population initialization
List <Krill> Krills = new List <Krill>();
for (int i = 1; i <= Parameters.Population; i++)
{
Krill krill = new Krill(i)
{
Coordinates = Vector <double> .Build.Random(Parameters.Dimensions, new ContinuousUniform(Parameters.LB, Parameters.UB))
};
Krills.Add(krill);
}
Population = new KrillPopulation(Krills);
}
/// <summary>
/// EQUATION 8
/// </summary>
private Vector <double> AlphaTarget(Krill krill, int currentIteration)
{
Krill bestKrill = KrillPopulation.GetBestKrill();
if (bestKrill.Fitness > krill.Fitness)
{
double K_i_best = K_i_j(krill.Fitness, bestKrill.Fitness);
Vector <double> X_i_best = X_i_j(krill.Coordinates, bestKrill.Coordinates);
double C_best = EffectiveCoefficient(currentIteration);
return(X_i_best.Multiply(C_best * K_i_best));
}
else
{
return(Vector <double> .Build.Dense(krill.Coordinates.Count));
}
}
public void Run(int evaluations, double C_t, double N_max, double V_f, double D_max)
{
var scaleVector = CalculateScaleVector(C_t, UB_vector, LB_vector);
InducedMotion inducedMotion = new InducedMotion(KrillPopulation, FitnessFunction, evaluations, N_max);
ForagingMotion foragingMotion = new ForagingMotion(KrillPopulation, FitnessFunction, evaluations, V_f);
VirtualFood virtualFood = new VirtualFood(KrillPopulation, FitnessFunction, UB_vector, LB_vector);
PhysicalDiffusion physicalDiffusion = new PhysicalDiffusion(D_max, evaluations, scaleVector.Count);
// We evaluate each krill in the population
KrillPopulation.EvaluatePopulation(FitnessFunction);
for (int i = 1; i <= evaluations; i++)
{
var vf_position = virtualFood.CreateVirtualFood();
foreach (var krill in KrillPopulation.Population)
{
Vector <double> N_i = inducedMotion.GetInducedMotion(krill, i);
Vector <double> F_i = foragingMotion.GetForagingMotion(krill, i, vf_position);
Vector <double> D_i = physicalDiffusion.GetPhysicalDiffusion(i);
Vector <double> X_i = (F_i + N_i).Add(D_i); // EQUATION 1
X_i = X_i.PointwiseMultiply(scaleVector);
var newPosition = krill.Coordinates + X_i;
var bestKrillPosition = KrillPopulation.GetBestKrill().Coordinates;
krill.Coordinates = MathHelpers.FindLimits(newPosition, bestKrillPosition, LB_vector, UB_vector);
}
// We evaluate each krill in the population
KrillPopulation.EvaluatePopulation(FitnessFunction);
OnGenerationComplete.Invoke(KrillPopulation, new RunEventArgs(i));
}
OnRunComplete.Invoke(KrillPopulation, new RunEventArgs(evaluations));
}
public Neighbourhood(KrillPopulation krillPopulation)
{
this.krillPopulation = krillPopulation;
}
public MotionBase(KrillPopulation KrillPopulation, FitnessFunction fitnessFunction)
{
this.KrillPopulation = KrillPopulation;
FitnessFunction = fitnessFunction;
}
void Krill_OnRunComplete(object sender, RunEventArgs e)
{
KrillPopulation population = (KrillPopulation)sender;
Console.WriteLine("Run complete");
}
