bool IndexPCalculator::InitializeImpl(const OptionsList& options,
const std::string& prefix)
{
DBG_START_METH("IndexPCalculator::InitializeImpl", dbg_verbosity);
SmartPtr<const IteratesVector> iv = IpData().curr();
nrows_ = 0;
for (Index i=0; i<iv->NComps(); ++i) {
nrows_+=iv->GetComp(i)->Dim();
}
data_A()->Print(Jnlst(),J_VECTOR,J_USER1,"PCalc SchurData");
return true;
}
ESymSolverStatus AugRestoSystemSolver::Solve(const SymMatrix* W,
double W_factor,
const Vector* D_x,
double delta_x,
const Vector* D_s,
double delta_s,
const Matrix* J_c,
const Vector* D_c,
double delta_c,
const Matrix* J_d,
const Vector* D_d,
double delta_d,
const Vector& rhs_x,
const Vector& rhs_s,
const Vector& rhs_c,
const Vector& rhs_d,
Vector& sol_x,
Vector& sol_s,
Vector& sol_c,
Vector& sol_d,
bool check_NegEVals,
Index numberOfNegEVals)
{
DBG_START_METH("AugRestoSystemSolver::Solve",dbg_verbosity);
DBG_ASSERT(J_c && J_d); // should pass these by ref
// I think the comment below is incorrect
// Remember, W and the D's may be NULL!
// ToDo: I don't think the W's can ever be NULL (we always need the structure)
DBG_ASSERT(W);
SmartPtr<const CompoundSymMatrix> CW =
static_cast<const CompoundSymMatrix*>(W);
SmartPtr<const CompoundVector> CD_x =
static_cast<const CompoundVector*>(D_x);
SmartPtr<const CompoundMatrix> CJ_c =
static_cast<const CompoundMatrix*>(J_c);
DBG_ASSERT(IsValid(CJ_c));
SmartPtr<const CompoundMatrix> CJ_d =
static_cast<const CompoundMatrix*>(J_d);
DBG_ASSERT(IsValid(CJ_d));
SmartPtr<const CompoundVector> Crhs_x =
static_cast<const CompoundVector*>(&rhs_x);
DBG_ASSERT(IsValid(Crhs_x));
SmartPtr<CompoundVector> Csol_x = static_cast<CompoundVector*>(&sol_x);
DBG_ASSERT(IsValid(Csol_x));
// Get the Sigma inverses
SmartPtr<const Vector> sigma_n_c;
SmartPtr<const Vector> sigma_p_c;
SmartPtr<const Vector> sigma_n_d;
SmartPtr<const Vector> sigma_p_d;
if (IsValid(CD_x)) {
sigma_n_c = CD_x->GetComp(1);
sigma_p_c = CD_x->GetComp(2);
sigma_n_d = CD_x->GetComp(3);
sigma_p_d = CD_x->GetComp(4);
}
SmartPtr<const Vector> sigma_tilde_n_c_inv =
Sigma_tilde_n_c_inv(sigma_n_c, delta_x, *Crhs_x->GetComp(1));
SmartPtr<const Vector> sigma_tilde_p_c_inv =
Sigma_tilde_p_c_inv(sigma_p_c, delta_x, *Crhs_x->GetComp(2));
SmartPtr<const Vector> sigma_tilde_n_d_inv =
Sigma_tilde_n_d_inv(sigma_n_d, delta_x, *Crhs_x->GetComp(3));
SmartPtr<const Vector> sigma_tilde_p_d_inv =
Sigma_tilde_p_d_inv(sigma_p_d, delta_x, *Crhs_x->GetComp(4));
// Pull out the expansion matrices for d
SmartPtr<const Matrix> pd_l = CJ_d->GetComp(0,3);
SmartPtr<const Matrix> neg_pd_u = CJ_d->GetComp(0,4);
// Now map the correct entries into the Solve method
// pull out the parts of the hessian h_orig + diag
DBG_PRINT_MATRIX(2, "CW", *CW);
SmartPtr<const SymMatrix> h_orig;
SmartPtr<const Vector> D_xR;
SmartPtr<const SumSymMatrix> WR_sum =
dynamic_cast<const SumSymMatrix*>(GetRawPtr(CW->GetComp(0,0)));
Number orig_W_factor = W_factor;
if (IsValid(WR_sum)) {
// We seem to be in the regular situation with exact second
// derivatives
double temp_factor;
WR_sum->GetTerm(0, temp_factor, h_orig);
DBG_ASSERT(temp_factor == 1. || temp_factor == 0.);
orig_W_factor = temp_factor * W_factor;
SmartPtr<const SymMatrix> eta_DR;
double factor;
WR_sum->GetTerm(1, factor, eta_DR);
SmartPtr<const Vector> wr_d =
static_cast<const DiagMatrix*>(GetRawPtr(eta_DR))->GetDiag();
if (IsValid(CD_x)) {
D_xR = D_x_plus_wr_d(CD_x->GetComp(0), factor, *wr_d);
}
else {
D_xR = D_x_plus_wr_d(NULL, factor, *wr_d);
}
}
else {
// Looks like limited memory quasi-Newton stuff
const LowRankUpdateSymMatrix* LR_W =
static_cast<const LowRankUpdateSymMatrix*>(GetRawPtr(CW->GetComp(0,0)));
DBG_ASSERT(LR_W);
h_orig = LR_W;
if (IsValid(CD_x)) {
D_xR = CD_x->GetComp(0);
}
else {
D_xR = NULL;
}
}
Number delta_xR = delta_x;
SmartPtr<const Vector> D_sR = D_s;
Number delta_sR = delta_s;
SmartPtr<const Matrix> J_cR = CJ_c->GetComp(0,0);
SmartPtr<const Vector> D_cR =
Neg_Omega_c_plus_D_c(sigma_tilde_n_c_inv, sigma_tilde_p_c_inv,
D_c, rhs_c);
DBG_PRINT((1,"D_cR tag = %d\n",D_cR->GetTag()));
Number delta_cR = delta_c;
SmartPtr<const Matrix> J_dR = CJ_d->GetComp(0,0);
SmartPtr<const Vector> D_dR =
Neg_Omega_d_plus_D_d(*pd_l, sigma_tilde_n_d_inv, *neg_pd_u,
sigma_tilde_p_d_inv, D_d, rhs_d);
Number delta_dR = delta_d;
SmartPtr<const Vector> rhs_xR = Crhs_x->GetComp(0);
SmartPtr<const Vector> rhs_sR = &rhs_s;
SmartPtr<const Vector> rhs_cR = Rhs_cR(rhs_c, sigma_tilde_n_c_inv,
*Crhs_x->GetComp(1),
sigma_tilde_p_c_inv,
*Crhs_x->GetComp(2));
SmartPtr<const Vector> rhs_dR = Rhs_dR(rhs_d, sigma_tilde_n_d_inv,
*Crhs_x->GetComp(3), *pd_l,
sigma_tilde_p_d_inv,
*Crhs_x->GetComp(4), *neg_pd_u);
SmartPtr<Vector> sol_xR = Csol_x->GetCompNonConst(0);
Vector& sol_sR = sol_s;
Vector& sol_cR = sol_c;
Vector& sol_dR = sol_d;
ESymSolverStatus status = orig_aug_solver_->Solve(GetRawPtr(h_orig),
orig_W_factor,
GetRawPtr(D_xR), delta_xR,
GetRawPtr(D_sR), delta_sR,
GetRawPtr(J_cR), GetRawPtr(D_cR),
delta_cR,
GetRawPtr(J_dR), GetRawPtr(D_dR),
delta_dR,
*rhs_xR, *rhs_sR, *rhs_cR, *rhs_dR,
*sol_xR, sol_sR, sol_cR, sol_dR,
check_NegEVals,
numberOfNegEVals);
if (status == SYMSOLVER_SUCCESS) {
// Now back out the solutions for the n and p variables
SmartPtr<Vector> sol_n_c = Csol_x->GetCompNonConst(1);
sol_n_c->Set(0.0);
if (IsValid(sigma_tilde_n_c_inv)) {
sol_n_c->AddTwoVectors(1., *Crhs_x->GetComp(1), -1.0, sol_cR, 0.);
sol_n_c->ElementWiseMultiply(*sigma_tilde_n_c_inv);
}
SmartPtr<Vector> sol_p_c = Csol_x->GetCompNonConst(2);
sol_p_c->Set(0.0);
if (IsValid(sigma_tilde_p_c_inv)) {
DBG_PRINT_VECTOR(2, "rhs_pc", *Crhs_x->GetComp(2));
DBG_PRINT_VECTOR(2, "delta_y_c", sol_cR);
DBG_PRINT_VECTOR(2, "Sig~_{p_c}^{-1}", *sigma_tilde_p_c_inv);
sol_p_c->AddTwoVectors(1., *Crhs_x->GetComp(2), 1.0, sol_cR, 0.);
sol_p_c->ElementWiseMultiply(*sigma_tilde_p_c_inv);
}
SmartPtr<Vector> sol_n_d = Csol_x->GetCompNonConst(3);
sol_n_d->Set(0.0);
if (IsValid(sigma_tilde_n_d_inv)) {
pd_l->TransMultVector(-1.0, sol_dR, 0.0, *sol_n_d);
sol_n_d->Axpy(1.0, *Crhs_x->GetComp(3));
sol_n_d->ElementWiseMultiply(*sigma_tilde_n_d_inv);
}
SmartPtr<Vector> sol_p_d = Csol_x->GetCompNonConst(4);
sol_p_d->Set(0.0);
if (IsValid(sigma_tilde_p_d_inv)) {
neg_pd_u->TransMultVector(-1.0, sol_dR, 0.0, *sol_p_d);
sol_p_d->Axpy(1.0, *Crhs_x->GetComp(4));
sol_p_d->ElementWiseMultiply(*sigma_tilde_p_d_inv);
}
}
return status;
}
bool
MinC_1NrmRestorationPhase::PerformRestoration()
{
DBG_START_METH("MinC_1NrmRestorationPhase::PerformRestoration",
dbg_verbosity);
// Increase counter for restoration phase calls
count_restorations_++;
Jnlst().Printf(J_DETAILED, J_MAIN,
"Starting Restoration Phase for the %d. time\n",
count_restorations_);
DBG_ASSERT(IpCq().curr_constraint_violation()>0.);
// ToDo set those up during initialize?
// Create the restoration phase NLP etc objects
SmartPtr<IpoptData> resto_ip_data = new IpoptData();
SmartPtr<IpoptNLP> resto_ip_nlp =
new RestoIpoptNLP(IpNLP(), IpData(), IpCq());
SmartPtr<IpoptCalculatedQuantities> resto_ip_cq =
new IpoptCalculatedQuantities(resto_ip_nlp, resto_ip_data);
// Determine if this is a square problem
bool square_problem = IpCq().IsSquareProblem();
// Decide if we want to use the original option or want to make
// some changes
SmartPtr<OptionsList> actual_resto_options = resto_options_;
if(square_problem) {
actual_resto_options = new OptionsList(*resto_options_);
// If this is a square problem, the want the restoration phase
// never to be left until the problem is converged
actual_resto_options->SetNumericValue("resto.required_infeasibility_reduction", 0.);
}
else if (expect_infeasible_problem_ && count_restorations_==1) {
if (IpCq().curr_constraint_violation()>1e-3) {
actual_resto_options = new OptionsList(*resto_options_);
// Ask for significant reduction of infeasibility, in the hope
// that we do not return from the restoration phase is the
// problem is infeasible
actual_resto_options->SetNumericValue("resto.required_infeasibility_reduction", 1e-3);
}
}
// Initialize the restoration phase algorithm
resto_alg_->Initialize(Jnlst(), *resto_ip_nlp, *resto_ip_data,
*resto_ip_cq, *actual_resto_options, "resto.");
// Set iteration counter and info field for the restoration phase
resto_ip_data->Set_iter_count(IpData().iter_count()+1);
resto_ip_data->Set_info_regu_x(IpData().info_regu_x());
resto_ip_data->Set_info_alpha_primal(IpData().info_alpha_primal());
resto_ip_data->Set_info_alpha_primal_char(IpData().info_alpha_primal_char());
resto_ip_data->Set_info_alpha_dual(IpData().info_alpha_dual());
resto_ip_data->Set_info_ls_count(IpData().info_ls_count());
// Call the optimization algorithm to solve the restoration phase
// problem
SolverReturn resto_status = resto_alg_->Optimize();
int retval=-1;
if (resto_status == SUCCESS) {
if (Jnlst().ProduceOutput(J_DETAILED, J_LINE_SEARCH)) {
Jnlst().Printf(J_DETAILED, J_LINE_SEARCH,
"\nRESTORATION PHASE RESULTS\n");
Jnlst().Printf(J_DETAILED, J_LINE_SEARCH,
"\n\nOptimal solution found! \n");
Jnlst().Printf(J_DETAILED, J_LINE_SEARCH,
"Optimal Objective Value = %.16E\n", resto_ip_cq->curr_f());
Jnlst().Printf(J_DETAILED, J_LINE_SEARCH,
"Number of Iterations = %d\n", resto_ip_data->iter_count());
}
if (Jnlst().ProduceOutput(J_VECTOR, J_LINE_SEARCH)) {
resto_ip_data->curr()->Print(Jnlst(), J_VECTOR, J_LINE_SEARCH, "curr");
}
retval = 0;
}
else if (resto_status == STOP_AT_TINY_STEP ||
resto_status == STOP_AT_ACCEPTABLE_POINT) {
Number orig_primal_inf =
IpCq().curr_primal_infeasibility(NORM_MAX);
// ToDo make the factor in following line an option
if (orig_primal_inf <= 1e2*IpData().tol()) {
Jnlst().Printf(J_WARNING, J_LINE_SEARCH,
"Restoration phase converged to a point with small primal infeasibility.\n");
THROW_EXCEPTION(RESTORATION_CONVERGED_TO_FEASIBLE_POINT,
"Restoration phase converged to a point with small primal infeasibility");
}
else {
THROW_EXCEPTION(LOCALLY_INFEASIBLE,
"Restoration phase converged to a point of local infeasibility");
}
}
else if (resto_status == MAXITER_EXCEEDED) {
THROW_EXCEPTION(RESTORATION_MAXITER_EXCEEDED,
"Maximal number of iterations exceeded in restoration phase.");
}
else if (resto_status == LOCAL_INFEASIBILITY) {
// converged to locally infeasible point - pass this on to the outer algorithm...
THROW_EXCEPTION(LOCALLY_INFEASIBLE, "Restoration phase converged to a point of local infeasibility");
}
else if (resto_status == RESTORATION_FAILURE) {
Jnlst().Printf(J_WARNING, J_LINE_SEARCH,
"Restoration phase in the restoration phase failed.\n");
THROW_EXCEPTION(RESTORATION_FAILED, "Restoration phase in the restoration phase failed.");
}
else if (resto_status == USER_REQUESTED_STOP) {
// Use requested stop during restoration phase - rethrow exception
THROW_EXCEPTION(RESTORATION_USER_STOP, "User requested stop during restoration phase");
}
else {
Jnlst().Printf(J_ERROR, J_MAIN, "Sorry, things failed ?!?!\n");
retval = 1;
}
if (retval == 0) {
// Copy the results into the trial fields;. They will be
// accepted later in the full algorithm
SmartPtr<const CompoundVector> cx =
dynamic_cast<const CompoundVector*>(GetRawPtr(resto_ip_data->curr()->x()));
DBG_ASSERT(IsValid(cx));
SmartPtr<IteratesVector> trial = IpData().trial()->MakeNewContainer();
trial->Set_primal(*cx->GetComp(0), *resto_ip_data->curr()->s());
IpData().set_trial(trial);
// If this is a square problem, we are done because a
// sufficiently feasible point has been found
if (square_problem) {
Jnlst().Printf(J_DETAILED, J_LINE_SEARCH,
"Recursive restoration phase algorithm termined successfully for square problem.\n");
IpData().AcceptTrialPoint();
THROW_EXCEPTION(FEASIBILITY_PROBLEM_SOLVED, "Restoration phase converged to sufficiently feasible point of original square problem.");
}
// Update the bound multiplers, pretending that the entire
// progress in x and s in the restoration phase has been one
// [rimal-dual Newton step (and therefore the result of solving
// an augmented system)
SmartPtr<IteratesVector> delta = IpData().curr()->MakeNewIteratesVector(true);
delta->Set(0.0);
ComputeBoundMultiplierStep(*delta->z_L_NonConst(), *IpData().curr()->z_L(),
*IpCq().curr_slack_x_L(),
*IpCq().trial_slack_x_L());
ComputeBoundMultiplierStep(*delta->z_U_NonConst(), *IpData().curr()->z_U(),
*IpCq().curr_slack_x_U(),
*IpCq().trial_slack_x_U());
ComputeBoundMultiplierStep(*delta->v_L_NonConst(), *IpData().curr()->v_L(),
*IpCq().curr_slack_s_L(),
*IpCq().trial_slack_s_L());
ComputeBoundMultiplierStep(*delta->v_U_NonConst(), *IpData().curr()->v_U(),
*IpCq().curr_slack_s_U(),
*IpCq().trial_slack_s_U());
DBG_PRINT_VECTOR(1, "delta_z_L", *delta->z_L());
DBG_PRINT_VECTOR(1, "delta_z_U", *delta->z_U());
DBG_PRINT_VECTOR(1, "delta_v_L", *delta->v_L());
DBG_PRINT_VECTOR(1, "delta_v_U", *delta->v_U());
Number alpha_dual = IpCq().dual_frac_to_the_bound(IpData().curr_tau(),
*delta->z_L_NonConst(),
*delta->z_U_NonConst(),
*delta->v_L_NonConst(),
*delta->v_U_NonConst());
Jnlst().Printf(J_DETAILED, J_LINE_SEARCH,
"Step size for bound multipliers: %8.2e\n", alpha_dual);
IpData().SetTrialBoundMultipliersFromStep(alpha_dual, *delta->z_L(), *delta->z_U(), *delta->v_L(), *delta->v_U() );
// ToDo: Check what to do here:
Number bound_mult_max = Max(IpData().trial()->z_L()->Amax(),
IpData().trial()->z_U()->Amax(),
IpData().trial()->v_L()->Amax(),
IpData().trial()->v_U()->Amax());
if (bound_mult_max > bound_mult_reset_threshold_) {
trial = IpData().trial()->MakeNewContainer();
Jnlst().Printf(J_DETAILED, J_LINE_SEARCH,
"Bound multipliers after restoration phase too large (max=%8.2e). Set all to 1.\n",
bound_mult_max);
trial->create_new_z_L();
trial->create_new_z_U();
trial->create_new_v_L();
trial->create_new_v_U();
trial->z_L_NonConst()->Set(1.0);
trial->z_U_NonConst()->Set(1.0);
trial->v_L_NonConst()->Set(1.0);
trial->v_U_NonConst()->Set(1.0);
IpData().set_trial(trial);
}
DefaultIterateInitializer::least_square_mults(
Jnlst(), IpNLP(), IpData(), IpCq(),
eq_mult_calculator_, constr_mult_reset_threshold_);
DBG_PRINT_VECTOR(2, "y_c", *IpData().curr()->y_c());
DBG_PRINT_VECTOR(2, "y_d", *IpData().curr()->y_d());
IpData().Set_iter_count(resto_ip_data->iter_count()-1);
// Skip the next line, because it would just replicate the first
// on during the restoration phase.
IpData().Set_info_skip_output(true);
}
return (retval == 0);
}