public Particle(ParticleSwarmOptimization us, Random r, Job job, bool maximize) : this()
{
Maximize = maximize;
BestValue = maximize ? float.MinValue : float.MaxValue;
Velocity = InitializeVelocity(us, r, job);
BestParameters = InitializeBestParameters(job);
Job = job;
}
private static float[] InitializeVelocity(ParticleSwarmOptimization us, Random r, Job job)
{
var parameters = job.Parameters;
float[] velocity = new float[parameters.Length];
// initialize all of the velocities to [-1,1] since we work in relative parameter space
for (int i = 0; i < velocity.Length; i++)
{
velocity[i] = us.MaxInitialVelocity * (float)((r.NextDouble() * 2.0) - 1.0);
}
return(velocity);
}
internal void UpdateVelocity(ParticleSwarmOptimization us, float[] globalBest, float[] bestInGeneration, Random r)
{
var parameters = us.Root.Parameters;
var factor = 1.0f - (us.Root.CurrentIteration / (us.Root.TotalIterations - 1.0f) * us.MovementReduction);
for (int i = 0; i < Velocity.Length; i++)
{
var bestParameterRandom = r.NextDouble();
var optimalRandom = r.NextDouble();
var current = Job.Parameters[i].Current;
var globalBestV = us.BestParameterWeight * bestParameterRandom * RelativeDistance(parameters[i], current, BestParameters[i]);
var localBestV = us.OptimalWeight * optimalRandom * RelativeDistance(parameters[i], current, globalBest[i]);
var generationBestV = us.GenerationOptimalWeight * RelativeDistance(parameters[i], current, bestInGeneration[i]);
// we step our velocity by apply a momentum to the old velocity and then applying the new with the rest of the fraction
Velocity[i] = ((factor * us.Momentum * Velocity[i]) + (float)(globalBestV + localBestV + generationBestV));
}
}
internal Job UpdatePosition(ParticleSwarmOptimization us)
{
var temp = Job.Parameters;
Job job = new Job();
job.Processed = false;
job.ProcessedBy = null;
job.Processing = false;
job.Value = float.NaN;
var parameters = job.Parameters = new ParameterSetting[temp.Length];
for (int i = 0; i < temp.Length; i++)
{
parameters[i] = new ParameterSetting();
// we need to move in real parameter space instead of relative parameter space
parameters[i].Current = temp[i].Current + Velocity[i] * (temp[i].Size);
// clamp the value inside of parameter space
if (parameters[i].Current < (parameters[i].Minimum = temp[i].Minimum))
{
parameters[i].Current = temp[i].Minimum;
if (us.Momentum > 0)
{
Velocity[i] = -Velocity[i];
}
}
if (parameters[i].Current > (parameters[i].Maximum = temp[i].Maximum))
{
parameters[i].Current = temp[i].Maximum;
if (us.Momentum > 0)
{
Velocity[i] = -Velocity[i];
}
}
}
return(Job = job);
}
internal void UpdateVelocity(ParticleSwarmOptimization us, float[] globalBest, float[] bestInGeneration, int ourIndex, Random r)
{
var parameters = us.Root.Parameters;
for(int i = 0; i < Velocity.Length; i++)
{
var bestParameterRandom = r.NextDouble();
var optimalRandom = r.NextDouble();
var generationRandom = r.NextDouble();
var current = Job.Parameters[i].Current;
var globalBestV = us.BestParameterWeight * bestParameterRandom * RelativeDistance(parameters[i], current, BestParameters[i]);
var localBestV = us.OptimalWeight * optimalRandom * RelativeDistance(parameters[i], current, globalBest[i]);
var generationBestV = us.GenerationOptimalWeight * RelativeDistance(parameters[i], current, bestInGeneration[i]);
// we step our velocity by apply a momentum to the old velocity and then applying the new with the rest of the fraction
Velocity[i] = (us.Momentum * Velocity[i]) + (float)(globalBestV + localBestV + generationBestV);
}
}
internal Job UpdatePosition(ParticleSwarmOptimization us)
{
var temp = Job.Parameters;
Job job = new Job();
job.Processed = false;
job.ProcessedBy = null;
job.Processing = false;
job.Value = float.NaN;
var parameters = job.Parameters = new ParameterSetting[temp.Length];
for(int i = 0; i < temp.Length; i++)
{
parameters[i] = new ParameterSetting();
// we need to move in real parameter space instead of relative parameter space
parameters[i].Current = temp[i].Current + Velocity[i] * (temp[i].Size);
// clamp the value inside of parameter space
if(parameters[i].Current < (parameters[i].Minimum = temp[i].Minimum))
{
parameters[i].Current = temp[i].Minimum;
Velocity[i] = -Velocity[i];
}
if(parameters[i].Current > (parameters[i].Maximum = temp[i].Maximum))
{
parameters[i].Current = temp[i].Maximum;
Velocity[i] = -Velocity[i];
}
}
return (Job = job);
}
internal Job UpdatePosition(ParticleSwarmOptimization us, Random rand)
{
var temp = Job.Parameters;
var job = new Job
{
Processed = false,
ProcessedBy = null,
Processing = false,
Value = float.NaN
};
var parameters = job.Parameters = new ParameterSetting[temp.Length];
for (int i = 0; i < temp.Length; i++)
{
parameters[i] = new ParameterSetting
{
// we need to move in real parameter space instead of relative parameter space
Current = temp[i].Current + Velocity[i] * (temp[i].Size)
};
// clamp the value inside of parameter space
if (parameters[i].Current < (parameters[i].Minimum = temp[i].Minimum))
{
// reflect off the boundary instead of being absorbed
switch (us.Bounce)
{
case BounceStrategy.Reflect:
parameters[i].Current = Math.Min(temp[i].Minimum + (temp[i].Minimum - parameters[i].Current), temp[i].Maximum);
break;
case BounceStrategy.RandomReallocation:
parameters[i].Current = (float)(rand.NextDouble() * (temp[i].Maximum - temp[i].Minimum) + temp[i].Minimum);
break;
case BounceStrategy.Absorb:
parameters[i].Current = parameters[i].Minimum;
break;
}
if (us.Momentum > 0)
{
Velocity[i] = -Velocity[i];
}
}
if (parameters[i].Current > (parameters[i].Maximum = temp[i].Maximum))
{
// reflect off the boundary instead of being absorbed
switch (us.Bounce)
{
case BounceStrategy.Reflect:
parameters[i].Current = Math.Max(temp[i].Maximum - (parameters[i].Current - temp[i].Maximum), temp[i].Minimum);
break;
case BounceStrategy.RandomReallocation:
parameters[i].Current = (float)(rand.NextDouble() * (temp[i].Maximum - temp[i].Minimum) + temp[i].Minimum);
break;
case BounceStrategy.Absorb:
parameters[i].Current = parameters[i].Maximum;
break;
}
if (us.Momentum > 0)
{
Velocity[i] = -Velocity[i];
}
}
}
return(Job = job);
}
