public NewtonSystem(QpProblem data, Variables initialPoint)
{
this.Q = data.Q;
this.A = data.A;
this.initialCholeskyFactor = this.Factorize(initialPoint);
}
public NewtonSystem(QpProblem data, Variables initialPoint)
{
this.Q = data.Q;
this.A = data.A;
this.initialCholeskyFactor = this.Factorize(initialPoint);
}
public QpProgressReport Solve(QpProblem data)
{
QpProgressReport report = this.preSolver.PreSolve();
if (report.SolveStatus != QpTerminationCode.InProgress)
{
return(report);
}
// Set up the problem from the warm start strategy
Variables currentIterate = this.warmStartStrategy.GenerateInitialPoint(data, report.X);
NewtonSystem newtonEquations = this.warmStartStrategy.InitialNewtonEquations;
Residuals residuals = this.warmStartStrategy.InitialResiduals;
double mu = currentIterate.Mu();
int count = 0;
do
{
// Analyse and report on the algorithm progress
report = this.statusReporter.DetermineProgress(currentIterate, residuals, mu, count);
this.publisher.Publish(report);
if (report.SolveStatus != QpTerminationCode.InProgress)
{
break;
}
// ~~~~~ Predictor Step ~~~~~
// Factorise the system of equations using a Newton method
ISolver <double> choleskyFactor = newtonEquations.Factorize(currentIterate, count);
Variables step = newtonEquations.ComputeStep(currentIterate, residuals, choleskyFactor);
// Calculate the largest permissable step length (alpha affine)
double alpha = currentIterate.GetLargestAlphaForStep(step);
// Calculate the complementarity measure and associated centering parameter.
double muAffine = currentIterate.MuGivenStep(step, alpha);
double sigma = Math.Pow(muAffine / mu, 3);
// ~~~~~ Corrector Step ~~~~~
// Apply second order step corrections and a re-centering adjustment.
residuals.ApplyCorrection(step, sigma, mu);
// Compute the corrected step and largest permitted step length.
step = newtonEquations.ComputeStep(currentIterate, residuals, choleskyFactor);
alpha = currentIterate.GetLargestAlphaForStep(step);
// Finally take the step and calculate the new complementarity measure.
currentIterate.ApplyStep(step, alpha);
residuals.Update(currentIterate);
mu = currentIterate.Mu();
count++;
} while (report.SolveStatus == QpTerminationCode.InProgress && count < 10000);
return(report);
}
private Variables BuildVariables(QpProblem problem, Vector<double> x)
{
double sqrtDataNorm = System.Math.Sqrt(problem.InfinityNorm());
Vector<double> z = Vector<double>.Build.Dense(problem.A.ColumnCount, sqrtDataNorm);
Vector<double> s = Vector<double>.Build.Dense(problem.A.ColumnCount, sqrtDataNorm);
return new Variables(x, z, s);
}
public Residuals(QpProblem data, Variables iterate)
{
this.Q = data.Q;
this.c = data.c;
this.A = data.A;
this.b = data.b;
this.Initialise();
this.Update(iterate);
}
private Variables BuildVariables(QpProblem problem, Vector <double> x)
{
double sqrtDataNorm = System.Math.Sqrt(problem.InfinityNorm());
Vector <double> z = Vector <double> .Build.Dense(problem.A.ColumnCount, sqrtDataNorm);
Vector <double> s = Vector <double> .Build.Dense(problem.A.ColumnCount, sqrtDataNorm);
return(new Variables(x, z, s));
}
public Residuals(QpProblem data, Variables iterate)
{
this.Q = data.Q;
this.c = data.c;
this.A = data.A;
this.b = data.b;
this.Initialise();
this.Update(iterate);
}
public Variables GenerateInitialPoint(QpProblem problem, Vector<double> x)
{
Vector<double> z = Vector<double>.Build.Dense(problem.A.ColumnCount, 1);
Vector<double> s = Vector<double>.Build.Dense(problem.A.ColumnCount, 1);
Variables initialPoint = new Variables(x, z, s);
this.startingResiduals = new Residuals(problem, initialPoint);
this.startingEquations = new NewtonSystem(problem, initialPoint);
return initialPoint;
}
public QpProgressReport Solve(QpProblem data)
{
QpProgressReport report = this.preSolver.PreSolve();
if (report.SolveStatus != QpTerminationCode.InProgress) return report;
// Set up the problem from the warm start strategy
Variables currentIterate = this.warmStartStrategy.GenerateInitialPoint(data, report.X);
NewtonSystem newtonEquations = this.warmStartStrategy.InitialNewtonEquations;
Residuals residuals = this.warmStartStrategy.InitialResiduals;
double mu = currentIterate.Mu();
int count = 0;
do
{
// Analyse and report on the algorithm progress
report = this.statusReporter.DetermineProgress(currentIterate, residuals, mu, count);
this.publisher.Publish(report);
if (report.SolveStatus != QpTerminationCode.InProgress) break;
// ~~~~~ Predictor Step ~~~~~
// Factorise the system of equations using a Newton method
ISolver<double> choleskyFactor = newtonEquations.Factorize(currentIterate, count);
Variables step = newtonEquations.ComputeStep(currentIterate, residuals, choleskyFactor);
// Calculate the largest permissable step length (alpha affine)
double alpha = currentIterate.GetLargestAlphaForStep(step);
// Calculate the complementarity measure and associated centering parameter.
double muAffine = currentIterate.MuGivenStep(step, alpha);
double sigma = Math.Pow(muAffine / mu, 3);
// ~~~~~ Corrector Step ~~~~~
// Apply second order step corrections and a re-centering adjustment.
residuals.ApplyCorrection(step, sigma, mu);
// Compute the corrected step and largest permitted step length.
step = newtonEquations.ComputeStep(currentIterate, residuals, choleskyFactor);
alpha = currentIterate.GetLargestAlphaForStep(step);
// Finally take the step and calculate the new complementarity measure.
currentIterate.ApplyStep(step, alpha);
residuals.Update(currentIterate);
mu = currentIterate.Mu();
count++;
} while (report.SolveStatus == QpTerminationCode.InProgress && count < 10000);
return report;
}
public Variables GenerateInitialPoint(QpProblem problem, Vector <double> x)
{
Vector <double> z = Vector <double> .Build.Dense(problem.A.ColumnCount, 1);
Vector <double> s = Vector <double> .Build.Dense(problem.A.ColumnCount, 1);
Variables initialPoint = new Variables(x, z, s);
this.startingResiduals = new Residuals(problem, initialPoint);
this.startingEquations = new NewtonSystem(problem, initialPoint);
return(initialPoint);
}
public Variables GenerateInitialPoint(QpProblem problem, Vector<double> x)
{
var initialPoint = this.BuildVariables(problem, x);
this.startingResiduals = new Residuals(problem, initialPoint);
this.startingEquations = new NewtonSystem(problem, initialPoint);
ISolver<double> choleskyFactor = this.startingEquations.InitialCholeskyFactor;
Variables step = this.startingEquations.ComputeStep(initialPoint, this.startingResiduals, choleskyFactor);
initialPoint.UpdateMultipliersWithoutViolation(step);
this.startingResiduals.Update(initialPoint);
return initialPoint;
}
public Variables GenerateInitialPoint(QpProblem problem, Vector <double> x)
{
var initialPoint = this.BuildVariables(problem, x);
this.startingResiduals = new Residuals(problem, initialPoint);
this.startingEquations = new NewtonSystem(problem, initialPoint);
ISolver <double> choleskyFactor = this.startingEquations.InitialCholeskyFactor;
Variables step = this.startingEquations.ComputeStep(initialPoint, this.startingResiduals, choleskyFactor);
initialPoint.UpdateMultipliersWithoutViolation(step);
this.startingResiduals.Update(initialPoint);
return(initialPoint);
}
public QpProgressAnalyser(QpProblem data, bool includeDeatiledReport)
{
this.dataInfinityNorm = data.InfinityNorm();
this.includeDetailedReport = includeDeatiledReport;
this.phiMinimumHistory = new double[MaxIterations];
}
public QpProgressAnalyser(QpProblem data, bool includeDeatiledReport)
{
this.dataInfinityNorm = data.InfinityNorm();
this.includeDetailedReport = includeDeatiledReport;
this.phiMinimumHistory = new double[MaxIterations];
}
