private double CalculateGCVelocityUpdate(PSO.Particle particle, PSO.Particle gbest, int i)
{
PSO.Settings settings = (PSO.Settings)Job.Optimizer.Configuration;
double ret;
// The idea here is to set the new particle position in an area around
// the best solution, while holding the constraint
// Cancel momentum update
ret = -particle.Velocity[i] * settings.Constriction;
// Reset position
ret -= particle.Parameters[i].Value;
// Move to particle best position
ret += gbest.Parameters[i].Value;
// Add random perturbation
string name = particle.Parameters[i].Name;
ConstraintMatrix cons = d_constraintsFor[name];
List <Linear.Vector> eqs = cons.NullspaceEquations;
int idx = cons.ParameterIndex(name);
// Generate random value on the null space of the constraints
for (int j = 0; j < eqs[idx].Count; ++j)
{
ret += cons.RN[j] * eqs[idx][j];
}
return(ret * Configuration.GuaranteedConvergence);
}
public double CalculateVelocityUpdate(PSO.Particle particle, PSO.Particle best, int i)
{
if (particle.Id != best.Id)
{
double multiplier = (double)particle.Data["dpso::multiplier"];
double up = particle.CalculateVelocityUpdate(best, i);
return((particle.Velocity[i] + up) * multiplier - up - particle.Velocity[i]);
}
double ret = 0;
// Special velocity update, first reset the position
ret -= particle.Parameters[i].Value;
// Then move the particle to its best position
ret += particle.PersonalBest.Parameters[i].Value;
// Finally, add the random sample search
Boundary boundary = particle.Parameters[i].Boundary;
ret += d_sampleSize * (boundary.Max - boundary.Min) * (1 - 2 * particle.State.Random.NextDouble());
return(ret);
}
public override void FromStorage(Storage.Storage storage, Storage.Records.Optimizer optimizer)
{
base.FromStorage(storage, optimizer);
uint priority = 0;
storage.Query("SELECT `expression`, `condition` FROM `stages` ORDER BY `id`", delegate(IDataReader reader)
{
string expression = Storage.Storage.As <string>(reader[0]);
string condition = Storage.Storage.As <string>(reader[1]);
d_stages.Add(new Stage(expression, condition, priority++));
return(true);
});
foreach (Solution sol in Job.Optimizer.Population)
{
UpdateFitnessStage(sol);
PSO.Particle p = (PSO.Particle)sol;
UpdateFitnessStage(p.PersonalBest);
}
UpdateFitnessStage(Job.Optimizer.Best);
Setup();
}
public void ValidateVelocityUpdate(PSO.Particle particle, double[] velocityUpdate)
{
// Make sure that we are within the parameter boundaries by linearly scaling the velocity vector (if needed)
foreach (ConstraintMatrix cons in d_constraints)
{
ValidateVelocityUpdate(particle, velocityUpdate, cons);
}
}
private void UpdateFitnessStage(Solution sol)
{
PSO.Particle p = (PSO.Particle)sol;
int stage = int.Parse(p.Data["StagePSO::stage"] as string);
p.Fitness.SetUserData("StagePSOStage", d_stages[stage]);
}
private bool ValidateConstraints()
{
double maxvel = ((PSO.Settings)Job.Optimizer.Configuration).MaxVelocity;
bool isok = true;
foreach (Solution solution in Job.Optimizer.Population)
{
PSO.Particle p = (PSO.Particle)solution;
for (int i = 0; i < solution.Parameters.Count; ++i)
{
Parameter param = solution.Parameters[i];
double mv = (param.Boundary.Max - param.Boundary.Min) * maxvel;
if (maxvel > 0 && ((PSO.Particle)solution).Velocity[i] > mv)
{
Console.WriteLine("Velocity boundary violated: {0} = {1}", param.Name, ((PSO.Particle)solution).Velocity[i]);
isok = false;
}
}
foreach (ConstraintMatrix cons in d_constraints)
{
Linear.Constraint constraint;
Dictionary <string, double> values = new Dictionary <string, double>();
foreach (Parameter param in solution.Parameters)
{
values[param.Name] = param.Value;
}
if (!cons.Validate(values, out constraint))
{
ConstraintViolationError("pos", cons, solution, values, constraint);
isok = false;
continue;
}
values.Clear();
for (int i = 0; i < p.Parameters.Count; ++i)
{
values[p.Parameters[i].Name] = p.Velocity[i];
}
if (!cons.ValidateNull(values, out constraint))
{
ConstraintViolationError("vel", cons, solution, values, constraint);
isok = false;
continue;
}
}
}
return(isok);
}
public PSO.State.VelocityUpdateType VelocityUpdateComponents(PSO.Particle particle)
{
if (particle.Id != Job.Optimizer.Best.Id)
{
// Use default update when not the best
return(PSO.State.VelocityUpdateType.Default);
}
else
{
// Keep the momentum
return(PSO.State.VelocityUpdateType.DisableGlobal | PSO.State.VelocityUpdateType.DisableLocal);
}
}
public double CalculateVelocityUpdate(PSO.Particle particle, PSO.Particle gbest, int i)
{
// If there are no constraints, then just use the default
double r1;
double r2;
Parameter parameter = particle.Parameters[i];
string name = parameter.Name;
if (d_constraintsFor.ContainsKey(name))
{
if (particle.Id == gbest.Id && Configuration.GuaranteedConvergence > 0)
{
return(CalculateGCVelocityUpdate(particle, gbest, i));
}
ConstraintMatrix cons = d_constraintsFor[name];
r1 = cons.R1[particle.Id];
r2 = cons.R2[particle.Id];
}
else
{
r1 = particle.State.Random.NextDouble();
r2 = particle.State.Random.NextDouble();
}
PSO.Settings settings = (PSO.Settings)Job.Optimizer.Configuration;
double pg = 0;
double pl = 0;
// Global best difference
if (gbest != null)
{
pg = gbest.Parameters[i].Value - parameter.Value;
}
// Local best difference
if (particle.PersonalBest != null)
{
pl = particle.PersonalBest.Parameters[i].Value - parameter.Value;
}
// PSO velocity update rule
return(settings.Constriction * (r1 * settings.CognitiveFactor * pl +
r2 * settings.SocialFactor * pg));
}
public override void Initialize(Solution solution)
{
base.Initialize(solution);
PSO.Particle p = (PSO.Particle)solution;
// Generate initial conditions to adhere to the constraints...
foreach (ConstraintMatrix cons in d_constraints)
{
Initialize(p, cons);
double[] vel = p.Velocity;
ValidateVelocityUpdate(p, vel, cons);
p.Velocity = vel;
}
}
public override void AfterUpdate()
{
base.AfterUpdate();
UpdateContext();
// Calculate swarm radius
double radius = SwarmRadius();
// Check stagnation
if (radius / d_diagonal >= d_stagnationThreshold.Evaluate(d_context, Biorob.Math.Constants.Context))
{
return;
}
// Regroup
double[] range = new double[Job.Optimizer.Parameters.Count];
range.Initialize();
Solution best = Job.Optimizer.Best;
for (int i = 0; i < range.Length; ++i)
{
foreach (Solution solution in Job.Optimizer.Population)
{
double dist = System.Math.Abs(solution.Parameters[i].Value - best.Parameters[i].Value);
if (dist > range[i])
{
range[i] = dist;
}
}
Boundary boundary = Job.Optimizer.Parameters[i].Boundary;
range[i] = System.Math.Min(boundary.Max - boundary.Min, d_regroupingFactor.Evaluate(d_context, Biorob.Math.Constants.Context) * range[i]);
}
// Reinitialize particles
foreach (Solution solution in Job.Optimizer.Population)
{
PSO.Particle particle = (PSO.Particle)solution;
for (int i = 0; i < particle.Parameters.Count; ++i)
{
particle.SetPosition(i, best.Parameters[i].Value + Job.Optimizer.State.Random.Range(-0.5, 0.5) * range[i]);
}
}
}
public int Compare(PSO.Particle p1, PSO.Particle p2)
{
if (p1 == null && p2 == null)
{
return(0);
}
else if (p1 == null)
{
return(-1);
}
else if (p2 == null)
{
return(1);
}
return(Compare(p1.Fitness, p2.Fitness));
}
public double CalculateVelocityUpdate(PSO.Particle particle, PSO.Particle best, int i)
{
if (particle.Id != best.Id)
{
// Only care about being the best
return(0.0);
}
double ret = 0;
// Special velocity update, first reset the position
ret -= particle.Parameters[i].Value;
// Then move the particle to its best position
ret += particle.PersonalBest.Parameters[i].Value;
// Finally, add the random sample search
Boundary boundary = particle.Parameters[i].Boundary;
ret += d_sampleSize * (boundary.Max - boundary.Min) * (1 - 2 * particle.State.Random.NextDouble());
return(ret);
}
public bool UpdateParticleBest(PSO.Particle particle)
{
particle.Data["dpso::multiplier"] = 1.0;
if (particle.PersonalBest == null || particle.Fitness > particle.PersonalBest.Fitness)
{
particle.Data["dpso::failures"] = 0;
particle.Data["dpso::multiplier"] = 1 / Configuration.EnergyInjectionFactor;
}
else
{
int failures = (int)(particle.Data["dpso::failures"]) + 1;
particle.Data["dpso::failures"] = failures;
if (failures > Configuration.FailureThreshold)
{
particle.Data["dpso::multiplier"] = Configuration.EnergyInjectionFactor;
particle.Data["dpso::failures"] = 0;
}
}
return(false);
}
public override void UpdateFitness(Solution solution)
{
base.UpdateFitness(solution);
PSO.Particle particle = (PSO.Particle)solution;
for (int i = 0; i < d_stages.Count; ++i)
{
Stage stage = d_stages[i];
Stage next = i != d_stages.Count - 1 ? d_stages[i + 1] : null;
if (next == null || !next.Validate(particle.Fitness.Context))
{
particle.Fitness.SetUserData("StagePSOStage", stage);
particle.Fitness.Value = stage.Value(particle.Fitness.Context);
particle.Data["StagePSO::stage"] = i;
particle.Data["StagePSO::waslast"] = particle.Data["StagePSO::islast"];
particle.Data["StagePSO::islast"] = (i == d_stages.Count - 1 ? "1" : "0");
break;
}
}
}
public bool UpdateParticleBest(PSO.Particle particle)
{
return(false);
}
public void ValidateVelocityUpdate(PSO.Particle particle, double[] velocityUpdate)
{
// Don't need to do anything special here
}
private void ValidateVelocityUpdate(PSO.Particle particle, double[] velocityUpdate, ConstraintMatrix cons)
{
double maxsc = -1;
double maxvel = ((PSO.Settings)Job.Optimizer.Configuration).MaxVelocity;
foreach (string name in cons.Parameters)
{
Parameter param = particle.Parameter(name);
int idx = particle.Parameters.IndexOf(param);
double newvel = velocityUpdate[idx];
double newpos = param.Value + newvel;
double sc = -1;
if (newvel == 0)
{
continue;
}
double maxpv = maxvel * (param.Boundary.Max - param.Boundary.Min);
if (maxvel > 0 && System.Math.Abs(newvel) > maxpv)
{
sc = System.Math.Abs(maxpv / newvel);
if (maxsc == -1 || sc < maxsc)
{
maxsc = sc;
}
}
if (newpos < param.Boundary.Min)
{
sc = System.Math.Abs((param.Boundary.Min - param.Value) / newvel);
}
else if (newpos > param.Boundary.Max)
{
sc = System.Math.Abs((param.Boundary.Max - param.Value) / newvel);
}
else if (sc == -1)
{
continue;
}
if (maxsc == -1 || (sc != -1 && sc < maxsc))
{
maxsc = sc;
}
}
if (maxsc != -1)
{
foreach (string name in cons.Parameters)
{
Parameter param = particle.Parameter(name);
int idx = particle.Parameters.IndexOf(param);
velocityUpdate[idx] *= maxsc;
/* This is a bit strange, but it is needed to solve numerical
* inaccuracies when multipying/dividing and we MUST ensure the
* boundaries (in particular if a sign would change) */
if (param.Value + velocityUpdate[idx] > param.Boundary.Max)
{
velocityUpdate[idx] = param.Boundary.Max - param.Value;
}
else if (param.Value + velocityUpdate[idx] < param.Boundary.Min)
{
velocityUpdate[idx] = param.Boundary.Min - param.Value;
}
}
}
}
public PSO.Particle GetUpdateBest(PSO.Particle particle)
{
return(null);
}
public PSO.State.VelocityUpdateType VelocityUpdateComponents(PSO.Particle particle)
{
return(PSO.State.VelocityUpdateType.DisableMomentum | PSO.State.VelocityUpdateType.DisableGlobal | PSO.State.VelocityUpdateType.DisableLocal);
}
public double Value(PSO.Particle particle)
{
return(Value(particle.Fitness));
}
public bool Validate(PSO.Particle particle)
{
return(Validate(particle.Fitness.Context, Biorob.Math.Constants.Context));
}
private void Initialize(PSO.Particle particle, ConstraintMatrix constraint)
{
List <Linear.Vector> eqs = constraint.Equations;
List <Linear.Vector> nulleqs = constraint.NullspaceEquations;
double[] rr = new double[eqs[0].Count];
double[] rrn = new double[nulleqs[0].Count];
double s = 0;
double sn = 0;
PSO.Settings settings = (PSO.Settings)Job.Optimizer.Configuration;
// Generate random variables
for (int i = 0; i < rr.Length; ++i)
{
rr[i] = particle.State.Random.NextDouble();
s += rr[i];
}
for (int i = 0; i < rrn.Length; ++i)
{
rrn[i] = particle.State.Random.NextDouble();
sn += rrn[i];
}
// Normalize such that sum == 1
for (int i = 0; i < rr.Length; ++i)
{
rr[i] /= s;
}
for (int i = 0; i < rrn.Length; ++i)
{
rrn[i] /= sn;
}
// Initialize parameters of particle according to linear equations
for (int i = 0; i < constraint.Parameters.Count; ++i)
{
string name = constraint.Parameters[i];
Parameter param = particle.Parameter(name);
double v = 0;
for (int j = 0; j < rr.Length; ++j)
{
v += rr[j] * constraint.Equations[i][j];
}
param.Value = v;
v = 0;
if (Configuration.HasInitialVelocity)
{
for (int j = 0; j < rrn.Length; ++j)
{
v += rrn[j] * constraint.NullspaceEquations[i][j];
}
if (settings.MaxVelocity > 0)
{
v *= settings.MaxVelocity;
}
}
int idx = particle.Parameters.IndexOf(param);
// Also set velocity to v
particle.SetVelocity(idx, v);
}
}
