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micpsolver_base.inl

/*-------------------------------------------------------------------------------
Copyright (c) 2014,2015 F. Georget <fabieng@princeton.edu>, Princeton University
All rights reserved.
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-----------------------------------------------------------------------------*/
#include "micpsolver_base.hpp" // syntaxic coloration
namespace specmicp {
namespace micpsolver {
// ref : Munson et al. (2001)
template <class program_t>
void MiCPSolverBaseProgram<program_t>::scaling_jacobian(
const Matrix& jacobian,
const Vector& residuals,
Vector& rscaler,
Vector& cscaler)
{
for (int i=0; i<jacobian.cols(); ++i)
{
const double sumhsq = jacobian.row(i).array().square().sum();
double s = std::sqrt(residuals(i)*residuals(i) + sumhsq);
rscaler(i) = 1.0/std::max(s, 1e-10);
}
for (int i=0; i<jacobian.cols(); ++i)
{
const double sumhsq = (rscaler.asDiagonal()*jacobian).col(i).array().square().sum();
double s = std::sqrt(sumhsq);
cscaler(i) = 1.0/std::max(s, 1e-10);
}
}
template <class program_t>
MiCPSolverReturnCode MiCPSolverBaseProgram<program_t>::check_convergence(
int nb_iterations,
const Vector& update,
const Vector& solution,
const Vector& residuals,
bool may_have_converged
)
{
MiCPSolverReturnCode termcode = MiCPSolverReturnCode::NotConvergedYet;
const scalar_t norm_residuals = residuals.lpNorm<Eigen::Infinity>();
if (norm_residuals < get_options().fvectol)
{
if (may_have_converged == true)
termcode = MiCPSolverReturnCode::ResidualMinimized;
}
else if (nb_iterations >0 and norm_update<Eigen::Infinity>(update, solution) < get_options().steptol)
{
if (norm_residuals > get_options().threshold_stationary_point)
{
ERROR << "Stationary point detected !";
termcode = MiCPSolverReturnCode::StationaryPoint;
}
if (may_have_converged == true)
{
WARNING << "MiCP solver : Error is minimized - may indicate a stationnary point";
termcode = MiCPSolverReturnCode::ErrorMinimized;
}
}
else if (nb_iterations > get_options().max_iter)
{
ERROR << "Maximum number of iteration reached (" << get_options().max_iter << ")";
termcode = MiCPSolverReturnCode::MaxIterations;
}
else if (get_perfs().max_taken)
{
++get_perfs().nb_consecutive_max_taken;
++get_perfs().nb_max_taken;
if (get_perfs().nb_consecutive_max_taken == get_options().maxiter_maxstep) {
ERROR << "Divergence detected - Maximum step length taken two many times";
termcode = MiCPSolverReturnCode::MaxStepTakenTooManyTimes;
}
}
else
{
get_perfs().nb_consecutive_max_taken = 0;
}
return termcode;
}
template <class program_t>
void MiCPSolverBaseProgram<program_t>::reformulate_jacobian_cck(
const Vector& x,
const Vector& r,
Matrix& jacobian
)
{
// set the z vector : contains 1 for degenerate points
Eigen::VectorXd z(Eigen::VectorXd::Zero(get_neq()));
for (index_t i=get_neq_free(); i<get_neq(); ++i)
{
if (x(i) == 0 and r(i) == 0)
z(i) = 1.0;
}
// modify the jacobian
const scalar_t lambda = get_options().penalization_factor;
for (index_t i=get_neq_free(); i<get_neq(); ++i)
{
if (z(i) != 0)
{
const scalar_t gpdotz = jacobian.row(i).dot(z);
scalar_t s = std::abs(z(i)) + std::abs(gpdotz);
const scalar_t ssquare = s*s;
s = s * std::sqrt((z(i)*z(i))/ssquare + (gpdotz*gpdotz)/ssquare);
const scalar_t c = lambda*(z(i)/s - 1);
const scalar_t d = lambda*(gpdotz/s -1);
jacobian.row(i) *= d;
jacobian(i, i) += c;
}
else
{
scalar_t s = std::abs(x(i)) + std::abs(r(i));
const scalar_t ssquare = s*s;
s = s * std::sqrt((x(i)*x(i))/ssquare + (r(i)*r(i))/ssquare);
scalar_t c = lambda*(x(i)/s - 1);
scalar_t d = lambda*(r(i)/s - 1);
if ((lambda <1) and (r(i) > 0) and (x(i) >0))
{
c -= (1-lambda)*r(i);
d -= (1-lambda)*x(i);
}
jacobian.row(i) *= d;
jacobian(i, i) += c;
}
}
}
// Projection of the variables onto the feasible set
template <class program_t>
void MiCPSolverBaseProgram<program_t>::projection(Vector& x)
{
for (index_t i=0; i<get_program()->nb_complementarity_variables(); ++i)
{
if (x(i+get_program()->nb_free_variables()) < get_options().projection_min_variable)
{
x(i+get_program()->nb_free_variables()) = 0;
}
}
}
template <class program_t>
scalar_t MiCPSolverBaseProgram<program_t>::is_step_too_long(Vector& update)
{
scalar_t steplength = update.norm();
if (steplength > get_options().maxstep)
{
get_perfs().max_taken = true;
update = get_options().maxstep / steplength * update;
steplength = get_options().maxstep;
}
return steplength;
}
} // end namespace micpsolver
} // end namespace specmicp

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