Number CGPenaltyCq::dT_times_barH_times_d()
{
DBG_START_METH("IpoptCalculatedQuantities::dT_times_barH_times_d()",
dbg_verbosity);
Number result;
SmartPtr<const Vector> d_x = CGPenData().delta_cgfast()->x();
SmartPtr<const Vector> d_s = CGPenData().delta_cgfast()->s();
SmartPtr<const Vector> y_c = ip_data_->curr()->y_c();
SmartPtr<const Vector> y_d = ip_data_->curr()->y_d();
SmartPtr<const Vector> dy_c = CGPenData().delta_cgfast()->y_c();
SmartPtr<const Vector> dy_d = CGPenData().delta_cgfast()->y_d();
SmartPtr<const Vector> c = ip_cq_->curr_c();
SmartPtr<const Vector> d_minus_s = ip_cq_->curr_d_minus_s();
Number deriv_barrier_dx = ip_cq_->curr_grad_barrier_obj_x()->Dot(*d_x);
Number deriv_barrier_dx_ds = deriv_barrier_dx + ip_cq_->curr_grad_barrier_obj_s()->Dot(*d_s);
Number penalty = CGPenData().curr_penalty();
result = -y_c->Dot(*dy_c);
result -= y_d->Dot(*dy_d);
result *= curr_cg_pert_fact();
result -= deriv_barrier_dx_ds;
result += c->Dot(*y_c);
result += d_minus_s->Dot(*y_d);
result -= c->Dot(*dy_c);
result -= d_minus_s->Dot(*dy_d);
result += penalty*ip_cq_->curr_primal_infeasibility(NORM_2);
return result;
}
Number CGPenaltyCq::curr_direct_deriv_penalty_function()
{
DBG_START_METH("CGPenaltyCq::curr_direct_deriv_penalty_function()",
dbg_verbosity);
Number result;
SmartPtr<const Vector> x = ip_data_->curr()->x();
SmartPtr<const Vector> s = ip_data_->curr()->s();
SmartPtr<const Vector> y_c = ip_data_->curr()->y_c();
SmartPtr<const Vector> y_d = ip_data_->curr()->y_d();
SmartPtr<const Vector> dy_c = CGPenData().delta_cgpen()->y_c();
SmartPtr<const Vector> dy_d = CGPenData().delta_cgpen()->y_d();
SmartPtr<const Vector> dx = CGPenData().delta_cgpen()->x();
SmartPtr<const Vector> ds = CGPenData().delta_cgpen()->s();
std::vector<const TaggedObject*> tdeps(8);
tdeps[0] = GetRawPtr(x);
tdeps[1] = GetRawPtr(s);
tdeps[2] = GetRawPtr(y_c);
tdeps[3] = GetRawPtr(y_d);
tdeps[4] = GetRawPtr(dy_c);
tdeps[5] = GetRawPtr(dy_d);
tdeps[6] = GetRawPtr(dx);
tdeps[7] = GetRawPtr(ds);
Number mu = ip_data_->curr_mu();
Number penalty = CGPenData().curr_penalty();
std::vector<Number> sdeps(2);
sdeps[0] = mu;
sdeps[1] = penalty;
if (!curr_direct_deriv_penalty_function_cache_.GetCachedResult(result, tdeps, sdeps)) {
result = ip_cq_->curr_grad_barrier_obj_x()->Dot(*dx) +
ip_cq_->curr_grad_barrier_obj_s()->Dot(*ds);
Number curr_inf = ip_cq_->curr_primal_infeasibility(NORM_2);
result -= penalty*curr_inf;
if (curr_inf != 0.) {
Number fac = penalty*CGPenData().CurrPenaltyPert()/curr_inf;
SmartPtr<const Vector> c = ip_cq_->curr_c();
SmartPtr<const Vector> d_minus_s = ip_cq_->curr_d_minus_s();
Number result1 = c->Dot(*y_c);
result1 += c->Dot(*dy_c);
result1 += d_minus_s->Dot(*y_d);
result1 += d_minus_s->Dot(*dy_d);
result1 *= fac;
result += result1;
}
curr_direct_deriv_penalty_function_cache_.AddCachedResult(result, tdeps, sdeps);
}
return result;
}
Number CGPenaltyCq::compute_curr_cg_penalty(const Number pen_des_fact )
{
DBG_START_METH("CGPenaltyCq::compute_curr_cg_penalty()",
dbg_verbosity);
SmartPtr<const Vector> d_x = ip_data_->delta()->x();
SmartPtr<const Vector> d_s = ip_data_->delta()->s();
SmartPtr<const Vector> y_c = ip_data_->curr()->y_c();
SmartPtr<const Vector> y_d = ip_data_->curr()->y_d();
SmartPtr<const Vector> dy_c = ip_data_->delta()->y_c();
SmartPtr<const Vector> dy_d = ip_data_->delta()->y_d();
// Compute delta barrier times (delta x, delta s)
Number deriv_barrier_dx = ip_cq_->curr_grad_barrier_obj_x()->Dot(*d_x);
Number deriv_barrier_dx_ds = deriv_barrier_dx + ip_cq_->curr_grad_barrier_obj_s()->Dot(*d_s);
// Compute delta x times the damped Hessian times delta x
SmartPtr<const Vector> tem_jac_cT_times_y_c =
ip_cq_->curr_jac_cT_times_vec(*y_c);
SmartPtr<const Vector> tem_jac_cT_times_dy_c =
ip_cq_->curr_jac_cT_times_vec(*dy_c);
SmartPtr<Vector> tem_jac_cT_times_y_c_plus_dy_c =
tem_jac_cT_times_y_c->MakeNew();
tem_jac_cT_times_y_c_plus_dy_c->AddTwoVectors(1.,*tem_jac_cT_times_y_c, 1.,
*tem_jac_cT_times_dy_c, 0.);
SmartPtr<const Vector> tem_jac_dT_times_y_d =
ip_cq_->curr_jac_dT_times_vec(*y_d);
SmartPtr<const Vector> tem_jac_dT_times_dy_d =
ip_cq_->curr_jac_cT_times_vec(*dy_c);
SmartPtr<Vector> tem_jac_dT_times_y_d_plus_dy_d =
tem_jac_cT_times_y_c->MakeNew();
tem_jac_dT_times_y_d_plus_dy_d->AddTwoVectors(1.,*tem_jac_dT_times_y_d, 1.,
*tem_jac_dT_times_dy_d, 0.);
Number d_xs_times_damped_Hessian_times_d_xs = -deriv_barrier_dx_ds;
d_xs_times_damped_Hessian_times_d_xs +=
-(tem_jac_cT_times_y_c_plus_dy_c->Dot(*d_x)
+tem_jac_dT_times_y_d_plus_dy_d->Dot(*d_x)
-y_d->Dot(*d_s)
-dy_d->Dot(*d_s));
Number dxs_nrm = pow(d_x->Nrm2(), 2.) + pow(d_s->Nrm2(), 2.);
d_xs_times_damped_Hessian_times_d_xs = Max(1e-8*dxs_nrm,
d_xs_times_damped_Hessian_times_d_xs);
Number infeasibility = ip_cq_->curr_primal_infeasibility(NORM_2);
Number penalty = 0.;
if (infeasibility > 0.) {
Number deriv_inf = 0.;
Number fac = CGPenData().CurrPenaltyPert()/infeasibility;
SmartPtr<const Vector> c = ip_cq_->curr_c();
SmartPtr<const Vector> d_minus_s = ip_cq_->curr_d_minus_s();
if (CGPenData().HaveCgFastDeltas()) {
SmartPtr<const Vector> fast_dy_c = CGPenData().delta_cgfast()->y_c();
SmartPtr<const Vector> fast_dy_d = CGPenData().delta_cgfast()->y_d();
deriv_inf += c->Dot(*fast_dy_c);
deriv_inf += d_minus_s->Dot(*fast_dy_d);
deriv_inf *= fac;
deriv_inf -= infeasibility;
}
else {
SmartPtr<const Vector> cgpen_dy_c = CGPenData().delta_cgpen()->y_c();
SmartPtr<const Vector> cgpen_dy_d = CGPenData().delta_cgpen()->y_d();
deriv_inf += c->Dot(*cgpen_dy_c);
deriv_inf += c->Dot(*y_c);
deriv_inf += d_minus_s->Dot(*cgpen_dy_d);
deriv_inf += d_minus_s->Dot(*y_d);
deriv_inf *= fac;
deriv_inf -= infeasibility;
}
penalty = -(deriv_barrier_dx_ds + pen_des_fact*
d_xs_times_damped_Hessian_times_d_xs)/
(deriv_inf + pen_des_fact*infeasibility);
}
return penalty;
}
Number InexactLSAcceptor::ComputeAlphaForY(
Number alpha_primal,
Number alpha_dual,
SmartPtr<IteratesVector>& delta
)
{
DBG_START_METH("InexactLSAcceptor::ComputeAlphaForY",
dbg_verbosity);
// Here, we choose as stepsize for y either alpha_primal, if the
// conditions from the ineqaxt paper is satisfied for it, or we
// compute the step size closest to alpha_primal but great than
// it, that does give the same progress as the full step would
// give.
Number alpha_y = alpha_primal;
SmartPtr<Vector> gx = IpCq().curr_grad_barrier_obj_x()->MakeNewCopy();
gx->AddTwoVectors(1., *IpCq().curr_jac_cT_times_curr_y_c(), 1., *IpCq().curr_jac_dT_times_curr_y_d(), 1.);
SmartPtr<Vector> Jxy = gx->MakeNew();
IpCq().curr_jac_c()->TransMultVector(1., *delta->y_c(), 0., *Jxy);
IpCq().curr_jac_d()->TransMultVector(1., *delta->y_d(), 1., *Jxy);
SmartPtr<const Vector> curr_scaling_slacks = InexCq().curr_scaling_slacks();
SmartPtr<Vector> gs = curr_scaling_slacks->MakeNew();
gs->AddTwoVectors(1., *IpCq().curr_grad_barrier_obj_s(), -1., *IpData().curr()->y_d(), 0.);
gs->ElementWiseMultiply(*curr_scaling_slacks);
SmartPtr<Vector> Sdy = delta->y_d()->MakeNewCopy();
Sdy->ElementWiseMultiply(*curr_scaling_slacks);
// using the magic formula in my notebook
Number a = pow(Jxy->Nrm2(), 2) + pow(Sdy->Nrm2(), 2);
Number b = 2 * (gx->Dot(*Jxy) - gs->Dot(*Sdy));
Number c = pow(gx->Nrm2(), 2) + pow(gs->Nrm2(), 2);
// First we check if the primal step size is good enough:
Number val_ap = alpha_primal * alpha_primal * a + alpha_primal * b + c;
Number val_1 = a + b + c;
if( val_ap <= val_1 )
{
Jnlst().Printf(J_DETAILED, J_LINE_SEARCH, " Step size for y: using alpha_primal\n.");
}
else
{
Number alpha_2 = -b / a - 1.;
Jnlst().Printf(J_DETAILED, J_LINE_SEARCH, " Step size for y candidate: %8.2e - ", alpha_2);
if( alpha_2 > alpha_primal && alpha_2 < 1. )
{
alpha_y = alpha_2;
Jnlst().Printf(J_DETAILED, J_LINE_SEARCH, "using that one\n.");
}
else
{
alpha_y = 1.;
Jnlst().Printf(J_DETAILED, J_LINE_SEARCH, "using 1 instead\n");
}
}
return alpha_y;
}
