public List <IParticle> Initialize(IProblem problem, int number)
{
List <IParticle> particles = new List <IParticle>(number);
for (int i = 0; i < number; i++)
{
StandardParticle particle = new StandardParticle();
particle.Parameters = Parameters;
particle.Initialize(problem);
particles.Add(particle);
}
return(particles);
}
public override void Adapt(PSO algorithm)
{
double avgVelocity = AverageAbsoluteVelocity(algorithm);
double idealVelocity = IdealVelocity(algorithm);
for (int i = 0; i < algorithm.SwarmSize; i++)
{
StandardParticle particle = algorithm.Particles[i] as StandardParticle;
double newInertia;
if (avgVelocity >= idealVelocity)
{
newInertia = Math.Max(particle.Parameters.InertiaWeight.Parameter - Delta, Minimum);
}
else
{
newInertia = Math.Min(particle.Parameters.InertiaWeight.Parameter + Delta, Maximum);
}
particle.Parameters.InertiaWeight = new ConstantControlParameter(newInertia);
}
}
/// <summary>
/// Calculate the velocity as an unbounded vector using the standard inertia weight model.
/// </summary>
/// <param name="particle">The particle to calculate velocity.</param>
/// <returns>An unbounded Vector containing the velocity.</returns>
public void UpdateVelocity(IParticle particle)
{
StandardParticle sp = particle as StandardParticle;
//TODO: update previous velocity
int dim = sp.Position.Length;
double w = sp.Parameters.InertiaWeight.Parameter;
double c1 = sp.Parameters.CognitiveAcceleration.Parameter;
double c2 = sp.Parameters.SocialAcceleration.Parameter;
Vector velocity = sp.Velocity;
Vector pos = sp.Position;
Vector lGuide = LocalGuiderProvider.GetGuide(sp);
Vector nGuide = NeighbourhoodGuideProvider.GetGuide(sp);
for (int i = 0; i < dim; i++)
{
double inertiaTerm = w * sp.Velocity[i];
double cognitiveTerm = c1 * RandomProvider.NextDouble() * (lGuide[i] - pos[i]);
double socialTerm = c2 * RandomProvider.NextDouble() * (nGuide[i] - pos[i]);
velocity[i] = inertiaTerm + cognitiveTerm + socialTerm;
}
}
