bool InexactSearchDirCalculator::InitializeImpl(
const OptionsList& options,
const std::string& prefix
)
{
options.GetNumericValue("local_inf_Ac_tol", local_inf_Ac_tol_, prefix);
Index enum_int;
options.GetEnumValue("inexact_step_decomposition", enum_int, prefix);
decomposition_type_ = DecompositionTypeEnum(enum_int);
bool compute_normal = false;
switch( decomposition_type_ )
{
case ALWAYS:
compute_normal = true;
break;
case ADAPTIVE:
case SWITCH_ONCE:
compute_normal = false;
break;
}
InexData().set_compute_normal(compute_normal);
InexData().set_next_compute_normal(compute_normal);
bool retval = inexact_pd_solver_->Initialize(Jnlst(), IpNLP(), IpData(), IpCq(), options, prefix);
if( !retval )
{
return false;
}
return normal_step_calculator_->Initialize(Jnlst(), IpNLP(), IpData(), IpCq(), options, prefix);
}
SmartPtr<AugSystemSolver> AlgorithmBuilder::AugSystemSolverFactory(
const Journalist& jnlst,
const OptionsList& options,
const std::string& prefix
)
{
SmartPtr<AugSystemSolver> AugSolver;
std::string linear_solver;
options.GetStringValue("linear_solver", linear_solver, prefix);
if( linear_solver == "custom" )
{
ASSERT_EXCEPTION(IsValid(custom_solver_), OPTION_INVALID, "Selected linear solver CUSTOM not available.");
AugSolver = custom_solver_;
}
else
{
AugSolver = new StdAugSystemSolver(*GetSymLinearSolver(jnlst, options, prefix));
}
Index enum_int;
options.GetEnumValue("hessian_approximation", enum_int, prefix);
HessianApproximationType hessian_approximation = HessianApproximationType(enum_int);
if( hessian_approximation == LIMITED_MEMORY )
{
std::string lm_aug_solver;
options.GetStringValue("limited_memory_aug_solver", lm_aug_solver, prefix);
if( lm_aug_solver == "sherman-morrison" )
{
AugSolver = new LowRankAugSystemSolver(*AugSolver);
}
else if( lm_aug_solver == "extended" )
{
Index lm_history;
options.GetIntegerValue("limited_memory_max_history", lm_history, prefix);
Index max_rank;
std::string lm_type;
options.GetStringValue("limited_memory_update_type", lm_type, prefix);
if( lm_type == "bfgs" )
{
max_rank = 2 * lm_history;
}
else if( lm_type == "sr1" )
{
max_rank = lm_history;
}
else
{
THROW_EXCEPTION(OPTION_INVALID, "Unknown value for option \"limited_memory_update_type\".");
}
AugSolver = new LowRankSSAugSystemSolver(*AugSolver, max_rank);
}
else
{
THROW_EXCEPTION(OPTION_INVALID, "Unknown value for option \"limited_memory_aug_solver\".");
}
}
return AugSolver;
}
bool OrigIterationOutput::InitializeImpl(const OptionsList& options,
const std::string& prefix)
{
options.GetBoolValue("print_info_string", print_info_string_, prefix);
Index enum_int;
options.GetEnumValue("inf_pr_output", enum_int, prefix);
inf_pr_output_ = InfPrOutput(enum_int);
return true;
}
bool RestoIterationOutput::InitializeImpl(const OptionsList& options,
const std::string& prefix)
{
options.GetBoolValue("print_info_string", print_info_string_, prefix);
Index enum_int;
options.GetEnumValue("inf_pr_output", enum_int, prefix);
inf_pr_output_ = InfPrOutput(enum_int);
bool retval = true;
if (IsValid(resto_orig_iteration_output_)) {
retval = resto_orig_iteration_output_->Initialize(Jnlst(), IpNLP(),
IpData(), IpCq(),
options, prefix);
}
return retval;
}
bool RestoIpoptNLP::Initialize(
const Journalist& jnlst,
const OptionsList& options,
const std::string& prefix
)
{
options.GetBoolValue("evaluate_orig_obj_at_resto_trial", evaluate_orig_obj_at_resto_trial_, prefix);
options.GetNumericValue("resto_penalty_parameter", rho_, prefix);
Index enum_int;
options.GetEnumValue("hessian_approximation", enum_int, prefix);
hessian_approximation_ = HessianApproximationType(enum_int);
options.GetNumericValue("resto_proximity_weight", eta_factor_, prefix);
initialized_ = true;
return IpoptNLP::Initialize(jnlst, options, prefix);
}
SmartPtr<HessianUpdater> AlgorithmBuilder::BuildHessianUpdater(
const Journalist& jnlst,
const OptionsList& options,
const std::string& prefix
)
{
// Get the Hessian updater for the main algorithm
SmartPtr<HessianUpdater> HessUpdater;
Index enum_int;
options.GetEnumValue("hessian_approximation", enum_int, prefix);
HessianApproximationType hessian_approximation = HessianApproximationType(enum_int);
switch( hessian_approximation )
{
case EXACT:
HessUpdater = new ExactHessianUpdater();
break;
case LIMITED_MEMORY:
// ToDo This needs to be replaced!
HessUpdater = new LimMemQuasiNewtonUpdater(false);
break;
}
return HessUpdater;
}
SmartPtr<IpoptAlgorithm>
AlgorithmBuilder::BuildBasicAlgorithm(const Journalist& jnlst,
const OptionsList& options,
const std::string& prefix)
{
DBG_START_FUN("AlgorithmBuilder::BuildBasicAlgorithm",
dbg_verbosity);
bool mehrotra_algorithm;
options.GetBoolValue("mehrotra_algorithm", mehrotra_algorithm, prefix);
// Create the convergence check
SmartPtr<ConvergenceCheck> convCheck =
new OptimalityErrorConvergenceCheck();
// Create the solvers that will be used by the main algorithm
SmartPtr<SparseSymLinearSolverInterface> SolverInterface;
std::string linear_solver;
options.GetStringValue("linear_solver", linear_solver, prefix);
bool use_custom_solver = false;
if (linear_solver=="ma27") {
#ifndef COINHSL_HAS_MA27
# ifdef HAVE_LINEARSOLVERLOADER
SolverInterface = new Ma27TSolverInterface();
if (!LSL_isMA27available()) {
char buf[256];
int rc = LSL_loadHSL(NULL, buf, 255);
if (rc) {
std::string errmsg;
errmsg = "Selected linear solver MA27 not available.\nTried to obtain MA27 from shared library \"";
errmsg += LSL_HSLLibraryName();
errmsg += "\", but the following error occured:\n";
errmsg += buf;
THROW_EXCEPTION(OPTION_INVALID, errmsg.c_str());
}
}
# else
THROW_EXCEPTION(OPTION_INVALID, "Support for MA27 has not been compiled into Ipopt.");
# endif
#else
SolverInterface = new Ma27TSolverInterface();
#endif
}
else if (linear_solver=="ma57") {
#ifndef COINHSL_HAS_MA57
# ifdef HAVE_LINEARSOLVERLOADER
SolverInterface = new Ma57TSolverInterface();
if (!LSL_isMA57available()) {
char buf[256];
int rc = LSL_loadHSL(NULL, buf, 255);
if (rc) {
std::string errmsg;
errmsg = "Selected linear solver MA57 not available.\nTried to obtain MA57 from shared library \"";
errmsg += LSL_HSLLibraryName();
errmsg += "\", but the following error occured:\n";
errmsg += buf;
THROW_EXCEPTION(OPTION_INVALID, errmsg.c_str());
}
}
# else
THROW_EXCEPTION(OPTION_INVALID, "Support for MA57 has not been compiled into Ipopt.");
# endif
#else
SolverInterface = new Ma57TSolverInterface();
#endif
}
else if (linear_solver=="ma77") {
#ifndef COINHSL_HAS_MA77
# ifdef HAVE_LINEARSOLVERLOADER
SolverInterface = new Ma77SolverInterface();
if (!LSL_isMA77available()) {
char buf[256];
int rc = LSL_loadHSL(NULL, buf, 255);
if (rc) {
std::string errmsg;
errmsg = "Selected linear solver HSL_MA77 not available.\nTried to obtain HSL_MA77 from shared library \"";
errmsg += LSL_HSLLibraryName();
errmsg += "\", but the following error occured:\n";
errmsg += buf;
THROW_EXCEPTION(OPTION_INVALID, errmsg.c_str());
}
}
# else
THROW_EXCEPTION(OPTION_INVALID, "Support for HSL_MA77 has not been compiled into Ipopt.");
# endif
#else
SolverInterface = new Ma77SolverInterface();
#endif
}
else if (linear_solver=="ma86") {
#ifndef COINHSL_HAS_MA86
# ifdef HAVE_LINEARSOLVERLOADER
SolverInterface = new Ma86SolverInterface();
if (!LSL_isMA86available()) {
char buf[256];
int rc = LSL_loadHSL(NULL, buf, 255);
if (rc) {
std::string errmsg;
errmsg = "Selected linear solver HSL_MA86 not available.\nTried to obtain HSL_MA86 from shared library \"";
errmsg += LSL_HSLLibraryName();
errmsg += "\", but the following error occured:\n";
errmsg += buf;
THROW_EXCEPTION(OPTION_INVALID, errmsg.c_str());
}
}
# else
THROW_EXCEPTION(OPTION_INVALID, "Support for HSL_MA86 has not been compiled into Ipopt.");
# endif
#else
SolverInterface = new Ma86SolverInterface();
#endif
}
else if (linear_solver=="pardiso") {
#ifndef HAVE_PARDISO
# ifdef HAVE_LINEARSOLVERLOADER
SolverInterface = new PardisoSolverInterface();
char buf[256];
int rc = LSL_loadPardisoLib(NULL, buf, 255);
if (rc) {
std::string errmsg;
errmsg = "Selected linear solver Pardiso not available.\nTried to obtain Pardiso from shared library \"";
errmsg += LSL_PardisoLibraryName();
errmsg += "\", but the following error occured:\n";
errmsg += buf;
THROW_EXCEPTION(OPTION_INVALID, errmsg.c_str());
}
# else
THROW_EXCEPTION(OPTION_INVALID, "Support for Pardiso has not been compiled into Ipopt.");
# endif
#else
SolverInterface = new PardisoSolverInterface();
#endif
}
else if (linear_solver=="ma97") {
#ifndef COINHSL_HAS_MA97
# ifdef HAVE_LINEARSOLVERLOADER
SolverInterface = new Ma97SolverInterface();
if (!LSL_isMA97available()) {
char buf[256];
int rc = LSL_loadHSL(NULL, buf, 255);
if (rc) {
std::string errmsg;
errmsg = "Selected linear solver HSL_MA97 not available.\nTried to obtain HSL_MA97 from shared library \"";
errmsg += LSL_HSLLibraryName();
errmsg += "\", but the following error occured:\n";
errmsg += buf;
THROW_EXCEPTION(OPTION_INVALID, errmsg.c_str());
}
}
# else
THROW_EXCEPTION(OPTION_INVALID, "Support for HSL_MA97 has not been compiled into Ipopt.");
# endif
#else
SolverInterface = new Ma97SolverInterface();
#endif
}
else if (linear_solver=="wsmp") {
#ifdef HAVE_WSMP
bool wsmp_iterative;
options.GetBoolValue("wsmp_iterative", wsmp_iterative, prefix);
if (wsmp_iterative) {
SolverInterface = new IterativeWsmpSolverInterface();
}
else {
SolverInterface = new WsmpSolverInterface();
}
#else
THROW_EXCEPTION(OPTION_INVALID,
"Selected linear solver WSMP not available.");
#endif
}
else if (linear_solver=="mumps") {
#ifdef COIN_HAS_MUMPS
SolverInterface = new MumpsSolverInterface();
#else
THROW_EXCEPTION(OPTION_INVALID,
"Selected linear solver MUMPS not available.");
#endif
}
else if (linear_solver=="custom") {
ASSERT_EXCEPTION(IsValid(custom_solver_), OPTION_INVALID,
"Selected linear solver CUSTOM not available.");
use_custom_solver = true;
}
SmartPtr<AugSystemSolver> AugSolver;
if (use_custom_solver) {
AugSolver = custom_solver_;
}
else {
SmartPtr<TSymScalingMethod> ScalingMethod;
std::string linear_system_scaling;
if (!options.GetStringValue("linear_system_scaling",
linear_system_scaling, prefix)) {
// By default, don't use mc19 for non-HSL solvers, or HSL_MA97
if (linear_solver!="ma27" && linear_solver!="ma57" && linear_solver!="ma77" && linear_solver!="ma86") {
linear_system_scaling="none";
}
}
if (linear_system_scaling=="mc19") {
#ifndef COINHSL_HAS_MC19
# ifdef HAVE_LINEARSOLVERLOADER
ScalingMethod = new Mc19TSymScalingMethod();
if (!LSL_isMC19available()) {
char buf[256];
int rc = LSL_loadHSL(NULL, buf, 255);
if (rc) {
std::string errmsg;
errmsg = "Selected linear system scaling method MC19 not available.\n";
errmsg += buf;
THROW_EXCEPTION(OPTION_INVALID, errmsg.c_str());
}
}
# else
THROW_EXCEPTION(OPTION_INVALID, "Support for MC19 has not been compiled into Ipopt.");
# endif
#else
ScalingMethod = new Mc19TSymScalingMethod();
#endif
}
else if (linear_system_scaling=="slack-based") {
ScalingMethod = new SlackBasedTSymScalingMethod();
}
SmartPtr<SymLinearSolver> ScaledSolver =
new TSymLinearSolver(SolverInterface, ScalingMethod);
AugSolver = new StdAugSystemSolver(*ScaledSolver);
}
Index enum_int;
options.GetEnumValue("hessian_approximation", enum_int, prefix);
HessianApproximationType hessian_approximation =
HessianApproximationType(enum_int);
if (hessian_approximation==LIMITED_MEMORY) {
std::string lm_aug_solver;
options.GetStringValue("limited_memory_aug_solver", lm_aug_solver,
prefix);
if (lm_aug_solver == "sherman-morrison") {
AugSolver = new LowRankAugSystemSolver(*AugSolver);
}
else if (lm_aug_solver == "extended") {
Index lm_history;
options.GetIntegerValue("limited_memory_max_history", lm_history,
prefix);
Index max_rank;
std::string lm_type;
options.GetStringValue("limited_memory_update_type", lm_type, prefix);
if (lm_type == "bfgs") {
max_rank = 2*lm_history;
}
else if (lm_type == "sr1") {
max_rank = lm_history;
}
else {
THROW_EXCEPTION(OPTION_INVALID, "Unknown value for option \"limited_memory_update_type\".");
}
AugSolver = new LowRankSSAugSystemSolver(*AugSolver, max_rank);
}
else {
THROW_EXCEPTION(OPTION_INVALID, "Unknown value for option \"limited_memory_aug_solver\".");
}
}
SmartPtr<PDPerturbationHandler> pertHandler;
std::string lsmethod;
options.GetStringValue("line_search_method", lsmethod, prefix);
if (lsmethod=="cg-penalty") {
pertHandler = new CGPerturbationHandler();
}
else {
pertHandler = new PDPerturbationHandler();
}
SmartPtr<PDSystemSolver> PDSolver =
new PDFullSpaceSolver(*AugSolver, *pertHandler);
// Create the object for initializing the iterates Initialization
// object. We include both the warm start and the defaut
// initializer, so that the warm start options can be activated
// without having to rebuild the algorithm
SmartPtr<EqMultiplierCalculator> EqMultCalculator =
new LeastSquareMultipliers(*AugSolver);
SmartPtr<IterateInitializer> WarmStartInitializer =
new WarmStartIterateInitializer();
SmartPtr<IterateInitializer> IterInitializer =
new DefaultIterateInitializer(EqMultCalculator, WarmStartInitializer,
AugSolver);
SmartPtr<RestorationPhase> resto_phase;
SmartPtr<RestoConvergenceCheck> resto_convCheck;
// We only need a restoration phase object if we use the filter
// line search
if (lsmethod=="filter" || lsmethod=="penalty") {
// Solver for the restoration phase
SmartPtr<AugSystemSolver> resto_AugSolver =
new AugRestoSystemSolver(*AugSolver);
SmartPtr<PDPerturbationHandler> resto_pertHandler =
new PDPerturbationHandler();
SmartPtr<PDSystemSolver> resto_PDSolver =
new PDFullSpaceSolver(*resto_AugSolver, *resto_pertHandler);
// Convergence check in the restoration phase
if (lsmethod=="filter") {
resto_convCheck = new RestoFilterConvergenceCheck();
}
else if (lsmethod=="penalty") {
resto_convCheck = new RestoPenaltyConvergenceCheck();
}
// Line search method for the restoration phase
SmartPtr<RestoRestorationPhase> resto_resto =
new RestoRestorationPhase();
SmartPtr<BacktrackingLSAcceptor> resto_LSacceptor;
std::string resto_lsacceptor;
options.GetStringValue("line_search_method", resto_lsacceptor,
"resto."+prefix);
if (resto_lsacceptor=="filter") {
resto_LSacceptor = new FilterLSAcceptor(GetRawPtr(resto_PDSolver));
}
else if (resto_lsacceptor=="cg-penalty") {
resto_LSacceptor = new CGPenaltyLSAcceptor(GetRawPtr(resto_PDSolver));
}
else if (resto_lsacceptor=="penalty") {
resto_LSacceptor = new PenaltyLSAcceptor(GetRawPtr(resto_PDSolver));
}
SmartPtr<LineSearch> resto_LineSearch =
new BacktrackingLineSearch(resto_LSacceptor, GetRawPtr(resto_resto),
GetRawPtr(resto_convCheck));
// Create the mu update that will be used by the restoration phase
// algorithm
SmartPtr<MuUpdate> resto_MuUpdate;
std::string resto_smuupdate;
if (!options.GetStringValue("mu_strategy", resto_smuupdate, "resto."+prefix)) {
// Change default for quasi-Newton option (then we use adaptive)
Index enum_int;
if (options.GetEnumValue("hessian_approximation", enum_int, prefix)) {
HessianApproximationType hessian_approximation =
HessianApproximationType(enum_int);
if (hessian_approximation==LIMITED_MEMORY) {
resto_smuupdate = "adaptive";
}
}
}
std::string resto_smuoracle;
std::string resto_sfixmuoracle;
if (resto_smuupdate=="adaptive" ) {
options.GetStringValue("mu_oracle", resto_smuoracle, "resto."+prefix);
options.GetStringValue("fixed_mu_oracle", resto_sfixmuoracle, "resto."+prefix);
}
if (resto_smuupdate=="monotone" ) {
resto_MuUpdate = new MonotoneMuUpdate(GetRawPtr(resto_LineSearch));
}
else if (resto_smuupdate=="adaptive") {
SmartPtr<MuOracle> resto_MuOracle;
if (resto_smuoracle=="loqo") {
resto_MuOracle = new LoqoMuOracle();
}
else if (resto_smuoracle=="probing") {
resto_MuOracle = new ProbingMuOracle(resto_PDSolver);
}
else if (resto_smuoracle=="quality-function") {
resto_MuOracle = new QualityFunctionMuOracle(resto_PDSolver);
}
SmartPtr<MuOracle> resto_FixMuOracle;
if (resto_sfixmuoracle=="loqo") {
resto_FixMuOracle = new LoqoMuOracle();
}
else if (resto_sfixmuoracle=="probing") {
resto_FixMuOracle = new ProbingMuOracle(resto_PDSolver);
}
else if (resto_sfixmuoracle=="quality-function") {
resto_FixMuOracle = new QualityFunctionMuOracle(resto_PDSolver);
}
else {
resto_FixMuOracle = NULL;
}
resto_MuUpdate =
new AdaptiveMuUpdate(GetRawPtr(resto_LineSearch),
resto_MuOracle, resto_FixMuOracle);
}
// Initialization of the iterates for the restoration phase
SmartPtr<EqMultiplierCalculator> resto_EqMultCalculator =
new LeastSquareMultipliers(*resto_AugSolver);
SmartPtr<IterateInitializer> resto_IterInitializer =
new RestoIterateInitializer(resto_EqMultCalculator);
// Create the object for the iteration output during restoration
SmartPtr<OrigIterationOutput> resto_OrigIterOutput = NULL;
// new OrigIterationOutput();
SmartPtr<IterationOutput> resto_IterOutput =
new RestoIterationOutput(resto_OrigIterOutput);
// Get the Hessian updater for the restoration phase
SmartPtr<HessianUpdater> resto_HessUpdater;
switch (hessian_approximation) {
case EXACT:
resto_HessUpdater = new ExactHessianUpdater();
break;
case LIMITED_MEMORY:
// ToDo This needs to be replaced!
resto_HessUpdater = new LimMemQuasiNewtonUpdater(true);
break;
}
// Put together the overall restoration phase IP algorithm
SmartPtr<SearchDirectionCalculator> resto_SearchDirCalc;
if (resto_lsacceptor=="cg-penalty") {
resto_SearchDirCalc = new CGSearchDirCalculator(GetRawPtr(resto_PDSolver));
}
else {
resto_SearchDirCalc = new PDSearchDirCalculator(GetRawPtr(resto_PDSolver));
}
SmartPtr<IpoptAlgorithm> resto_alg =
new IpoptAlgorithm(resto_SearchDirCalc,
GetRawPtr(resto_LineSearch),
GetRawPtr(resto_MuUpdate),
GetRawPtr(resto_convCheck),
resto_IterInitializer,
resto_IterOutput,
resto_HessUpdater,
resto_EqMultCalculator);
// Set the restoration phase
resto_phase =
new MinC_1NrmRestorationPhase(*resto_alg, EqMultCalculator);
}
// Create the line search to be used by the main algorithm
SmartPtr<BacktrackingLSAcceptor> LSacceptor;
if (lsmethod=="filter") {
LSacceptor = new FilterLSAcceptor(GetRawPtr(PDSolver));
}
else if (lsmethod=="cg-penalty") {
LSacceptor = new CGPenaltyLSAcceptor(GetRawPtr(PDSolver));
}
else if (lsmethod=="penalty") {
LSacceptor = new PenaltyLSAcceptor(GetRawPtr(PDSolver));
}
SmartPtr<LineSearch> lineSearch =
new BacktrackingLineSearch(LSacceptor,
GetRawPtr(resto_phase), convCheck);
// The following cross reference is not good: We have to store a
// pointer to the lineSearch object in resto_convCheck as a
// non-SmartPtr to make sure that things are properly deleted when
// the IpoptAlgorithm return by the Builder is destructed.
if (IsValid(resto_convCheck)) {
resto_convCheck->SetOrigLSAcceptor(*LSacceptor);
}
// Create the mu update that will be used by the main algorithm
SmartPtr<MuUpdate> MuUpdate;
std::string smuupdate;
if (!options.GetStringValue("mu_strategy", smuupdate, prefix)) {
// Change default for quasi-Newton option (then we use adaptive)
Index enum_int;
if (options.GetEnumValue("hessian_approximation", enum_int, prefix)) {
HessianApproximationType hessian_approximation =
HessianApproximationType(enum_int);
if (hessian_approximation==LIMITED_MEMORY) {
smuupdate = "adaptive";
}
}
if (mehrotra_algorithm)
smuupdate = "adaptive";
}
ASSERT_EXCEPTION(!mehrotra_algorithm || smuupdate=="adaptive",
OPTION_INVALID,
"If mehrotra_algorithm=yes, mu_strategy must be \"adaptive\".");
std::string smuoracle;
std::string sfixmuoracle;
if (smuupdate=="adaptive" ) {
if (!options.GetStringValue("mu_oracle", smuoracle, prefix)) {
if (mehrotra_algorithm)
smuoracle = "probing";
}
options.GetStringValue("fixed_mu_oracle", sfixmuoracle, prefix);
ASSERT_EXCEPTION(!mehrotra_algorithm || smuoracle=="probing",
OPTION_INVALID,
"If mehrotra_algorithm=yes, mu_oracle must be \"probing\".");
}
if (smuupdate=="monotone" ) {
MuUpdate = new MonotoneMuUpdate(GetRawPtr(lineSearch));
}
else if (smuupdate=="adaptive") {
SmartPtr<MuOracle> muOracle;
if (smuoracle=="loqo") {
muOracle = new LoqoMuOracle();
}
else if (smuoracle=="probing") {
muOracle = new ProbingMuOracle(PDSolver);
}
else if (smuoracle=="quality-function") {
muOracle = new QualityFunctionMuOracle(PDSolver);
}
SmartPtr<MuOracle> FixMuOracle;
if (sfixmuoracle=="loqo") {
FixMuOracle = new LoqoMuOracle();
}
else if (sfixmuoracle=="probing") {
FixMuOracle = new ProbingMuOracle(PDSolver);
}
else if (sfixmuoracle=="quality-function") {
FixMuOracle = new QualityFunctionMuOracle(PDSolver);
}
else {
FixMuOracle = NULL;
}
MuUpdate = new AdaptiveMuUpdate(GetRawPtr(lineSearch),
muOracle, FixMuOracle);
}
// Create the object for the iteration output
SmartPtr<IterationOutput> IterOutput =
new OrigIterationOutput();
// Get the Hessian updater for the main algorithm
SmartPtr<HessianUpdater> HessUpdater;
switch (hessian_approximation) {
case EXACT:
HessUpdater = new ExactHessianUpdater();
break;
case LIMITED_MEMORY:
// ToDo This needs to be replaced!
HessUpdater = new LimMemQuasiNewtonUpdater(false);
break;
}
// Create the main algorithm
SmartPtr<SearchDirectionCalculator> SearchDirCalc;
if (lsmethod=="cg-penalty") {
SearchDirCalc = new CGSearchDirCalculator(GetRawPtr(PDSolver));
}
else {
SearchDirCalc = new PDSearchDirCalculator(GetRawPtr(PDSolver));
}
SmartPtr<IpoptAlgorithm> alg =
new IpoptAlgorithm(SearchDirCalc,
GetRawPtr(lineSearch), MuUpdate,
convCheck, IterInitializer, IterOutput,
HessUpdater, EqMultCalculator);
return alg;
}
bool IterativePardisoSolverInterface::InitializeImpl(const OptionsList& options,
const std::string& prefix)
{
Index enum_int;
options.GetEnumValue("pardiso_matching_strategy", enum_int, prefix);
match_strat_ = PardisoMatchingStrategy(enum_int);
options.GetBoolValue("pardiso_redo_symbolic_fact_only_if_inertia_wrong",
pardiso_redo_symbolic_fact_only_if_inertia_wrong_,
prefix);
options.GetBoolValue("pardiso_repeated_perturbation_means_singular",
pardiso_repeated_perturbation_means_singular_,
prefix);
Index pardiso_out_of_core_power;
options.GetIntegerValue("pardiso_out_of_core_power",
pardiso_out_of_core_power, prefix);
options.GetBoolValue("pardiso_skip_inertia_check",
skip_inertia_check_, prefix);
// PD system
options.GetIntegerValue("pardiso_max_iter", pardiso_max_iter_, prefix);
options.GetNumericValue("pardiso_iter_relative_tol",
pardiso_iter_relative_tol_, prefix);
options.GetIntegerValue("pardiso_iter_coarse_size",
pardiso_iter_coarse_size_, prefix);
options.GetIntegerValue("pardiso_iter_max_levels",
pardiso_iter_max_levels_, prefix);
options.GetNumericValue("pardiso_iter_dropping_factor",
pardiso_iter_dropping_factor_, prefix);
options.GetNumericValue("pardiso_iter_dropping_schur",
pardiso_iter_dropping_schur_, prefix);
options.GetIntegerValue("pardiso_iter_max_row_fill",
pardiso_iter_max_row_fill_, prefix);
options.GetNumericValue("pardiso_iter_inverse_norm_factor",
pardiso_iter_inverse_norm_factor_, prefix);
// Normal system
options.GetIntegerValue("pardiso_max_iter", normal_pardiso_max_iter_,
prefix+"normal.");
options.GetNumericValue("pardiso_iter_relative_tol",
normal_pardiso_iter_relative_tol_,
prefix+"normal.");
options.GetIntegerValue("pardiso_iter_coarse_size",
normal_pardiso_iter_coarse_size_,
prefix+"normal.");
options.GetIntegerValue("pardiso_iter_max_levels",
normal_pardiso_iter_max_levels_,
prefix+"normal.");
options.GetNumericValue("pardiso_iter_dropping_factor",
normal_pardiso_iter_dropping_factor_,
prefix+"normal.");
options.GetNumericValue("pardiso_iter_dropping_schur",
normal_pardiso_iter_dropping_schur_,
prefix+"normal.");
options.GetIntegerValue("pardiso_iter_max_row_fill",
normal_pardiso_iter_max_row_fill_,
prefix+"normal.");
options.GetNumericValue("pardiso_iter_inverse_norm_factor",
normal_pardiso_iter_inverse_norm_factor_,
prefix+"normal.");
int pardiso_msglvl;
options.GetIntegerValue("pardiso_msglvl", pardiso_msglvl, prefix);
options.GetIntegerValue("pardiso_max_droptol_corrections",
pardiso_max_droptol_corrections_, prefix);
// Number value = 0.0;
// Tell Pardiso to release all memory if it had been used before
if (initialized_) {
ipfint PHASE = -1;
ipfint N = dim_;
ipfint NRHS = 0;
ipfint ERROR;
ipfint idmy;
double ddmy;
F77_FUNC(pardiso,PARDISO)(PT_, &MAXFCT_, &MNUM_, &MTYPE_, &PHASE, &N,
&ddmy, &idmy, &idmy, &idmy, &NRHS, IPARM_,
&MSGLVL_, &ddmy, &ddmy, &ERROR, DPARM_) ;
DBG_ASSERT(ERROR==0);
}
// Reset all private data
dim_=0;
nonzeros_=0;
have_symbolic_factorization_=false;
initialized_=false;
delete[] a_;
a_ = NULL;
#ifdef HAVE_PARDISO_OLDINTERFACE
THROW_EXCEPTION(OPTION_INVALID, "The inexact version works only with a new version of Pardiso (at least 4.0)");
#endif
// Call Pardiso's initialization routine
IPARM_[0] = 0; // Tell it to fill IPARM with default values(?)
ipfint ERROR = 0;
ipfint SOLVER = 1; // initialze only direct solver
F77_FUNC(pardisoinit,PARDISOINIT)(PT_, &MTYPE_, &SOLVER,
IPARM_, DPARM_, &ERROR);
// Set some parameters for Pardiso
IPARM_[0] = 1; // Don't use the default values
#if defined(HAVE_PARDISO_PARALLEL) || ! defined(HAVE_PARDISO)
// Obtain the numbers of processors from the value of OMP_NUM_THREADS
char *var = getenv("OMP_NUM_THREADS");
int num_procs = 1;
if (var != NULL) {
sscanf( var, "%d", &num_procs );
if (num_procs < 1) {
Jnlst().Printf(J_ERROR, J_LINEAR_ALGEBRA,
"Invalid value for OMP_NUM_THREADS (\"%s\").\n", var);
return false;
}
Jnlst().Printf(J_DETAILED, J_LINEAR_ALGEBRA,
"Using environment OMP_NUM_THREADS = %d as the number of processors.\n", num_procs);
}
#ifdef HAVE_PARDISO
// If we run Pardiso through the linear solver loader,
// we do not know whether it is the parallel version, so we do not report an error if OMP_NUM_THREADS is not set.
else {
Jnlst().Printf(J_ERROR, J_LINEAR_ALGEBRA,
"You need to set environment variable OMP_NUM_THREADS to the number of processors used in Pardiso (e.g., 1).\n\n");
return false;
}
#endif
IPARM_[2] = num_procs; // Set the number of processors
#else
IPARM_[2] = 1;
#endif
IPARM_[1] = 5;
IPARM_[5] = 1; // Overwrite right-hand side
// ToDo: decide if we need iterative refinement in Pardiso. For
// now, switch it off ?
IPARM_[7] = 0;
// Options suggested by Olaf Schenk
IPARM_[9] = 12;
IPARM_[10] = 2; // Results in better scaling
// Matching information: IPARM_[12] = 1 seems ok, but results in a
// large number of pivot perturbation
// Matching information: IPARM_[12] = 2 robust, but more expensive method
IPARM_[12] = (int)match_strat_;
Jnlst().Printf(J_DETAILED, J_LINEAR_ALGEBRA,
"Pardiso matching strategy (IPARM(13)): %d\n", IPARM_[12]);
IPARM_[20] = 3; // Results in better accuracy
IPARM_[23] = 1; // parallel fac
IPARM_[24] = 1; // parallel solve
IPARM_[28] = 0; // 32-bit factorization
IPARM_[29] = 1; // we need this for IPOPT interface
IPARM_[31] = 1 ; // iterative solver
MSGLVL_ = pardiso_msglvl;
pardiso_iter_dropping_factor_used_ = pardiso_iter_dropping_factor_;
pardiso_iter_dropping_schur_used_ = pardiso_iter_dropping_schur_;
normal_pardiso_iter_dropping_factor_used_ = normal_pardiso_iter_dropping_factor_;
normal_pardiso_iter_dropping_schur_used_ = normal_pardiso_iter_dropping_schur_;
// TODO Make option
decr_factor_ = 1./3.;
// Option for the out of core variant
// IPARM_[49] = pardiso_out_of_core_power;
SetIpoptCallbackFunction(&IpoptTerminationTest);
bool retval = normal_tester_->Initialize(Jnlst(), IpNLP(), IpData(),
IpCq(), options, prefix);
if (retval) {
retval = pd_tester_->Initialize(Jnlst(), IpNLP(), IpData(),
IpCq(), options, prefix);
}
return retval;
}
bool AdaptiveMuUpdate::InitializeImpl(const OptionsList& options,
const std::string& prefix)
{
options.GetNumericValue("mu_max_fact", mu_max_fact_, prefix);
if (!options.GetNumericValue("mu_max", mu_max_, prefix)) {
// Set to a negative value as a hint that this value still has
// to be computed
mu_max_ = -1.;
}
options.GetNumericValue("tau_min", tau_min_, prefix);
options.GetNumericValue("adaptive_mu_safeguard_factor", adaptive_mu_safeguard_factor_, prefix);
options.GetNumericValue("adaptive_mu_kkterror_red_fact", refs_red_fact_, prefix);
options.GetIntegerValue("adaptive_mu_kkterror_red_iters", num_refs_max_, prefix);
Index enum_int;
options.GetEnumValue("adaptive_mu_globalization", enum_int, prefix);
adaptive_mu_globalization_ = AdaptiveMuGlobalizationEnum(enum_int);
options.GetNumericValue("filter_max_margin", filter_max_margin_, prefix);
options.GetNumericValue("filter_margin_fact", filter_margin_fact_, prefix);
options.GetBoolValue("adaptive_mu_restore_previous_iterate", restore_accepted_iterate_, prefix);
bool retvalue = free_mu_oracle_->Initialize(Jnlst(), IpNLP(), IpData(),
IpCq(), options, prefix);
if (!retvalue) {
return retvalue;
}
if (IsValid(fix_mu_oracle_)) {
retvalue = fix_mu_oracle_->Initialize(Jnlst(), IpNLP(), IpData(),
IpCq(), options, prefix);
if (!retvalue) {
return retvalue;
}
}
options.GetNumericValue("adaptive_mu_monotone_init_factor", adaptive_mu_monotone_init_factor_, prefix);
options.GetNumericValue("barrier_tol_factor", barrier_tol_factor_, prefix);
options.GetNumericValue("mu_linear_decrease_factor", mu_linear_decrease_factor_, prefix);
options.GetNumericValue("mu_superlinear_decrease_power", mu_superlinear_decrease_power_, prefix);
options.GetEnumValue("quality_function_norm_type", enum_int, prefix);
adaptive_mu_kkt_norm_ = QualityFunctionMuOracle::NormEnum(enum_int);
options.GetEnumValue("quality_function_centrality", enum_int, prefix);
adaptive_mu_kkt_centrality_ = QualityFunctionMuOracle::CentralityEnum(enum_int);
options.GetEnumValue("quality_function_balancing_term", enum_int, prefix);
adaptive_mu_kkt_balancing_term_ = QualityFunctionMuOracle::BalancingTermEnum(enum_int);
options.GetNumericValue("compl_inf_tol", compl_inf_tol_, prefix);
if (prefix == "resto.") {
if (!options.GetNumericValue("mu_min", mu_min_, prefix)) {
// For restoration phase, we choose a more conservative mu_min
mu_min_ = 1e2*mu_min_;
// Compute mu_min based on tolerance (once the NLP scaling is known)
mu_min_default_ = true;
}
else {
mu_min_default_ = false;
}
}
else {
if (!options.GetNumericValue("mu_min", mu_min_, prefix)) {
// Compute mu_min based on tolerance (once the NLP scaling is known)
mu_min_default_ = true;
}
else {
mu_min_default_ = false;
}
}
options.GetNumericValue("mu_target", mu_target_, prefix);
init_dual_inf_ = -1.;
init_primal_inf_ = -1.;
refs_vals_.clear();
check_if_no_bounds_ = false;
no_bounds_ = false;
filter_.Clear();
IpData().SetFreeMuMode(true);
accepted_point_ = NULL;
// The following lines are only here so that
// IpoptCalculatedQuantities::CalculateSafeSlack and the first
// output line have something to work with
IpData().Set_mu(1.);
IpData().Set_tau(0.);
return retvalue;
}
bool PardisoSolverInterface::InitializeImpl(const OptionsList& options,
const std::string& prefix)
{
Index enum_int;
options.GetEnumValue("pardiso_matching_strategy", enum_int, prefix);
match_strat_ = PardisoMatchingStrategy(enum_int);
options.GetBoolValue("pardiso_redo_symbolic_fact_only_if_inertia_wrong",
pardiso_redo_symbolic_fact_only_if_inertia_wrong_,
prefix);
options.GetBoolValue("pardiso_repeated_perturbation_means_singular",
pardiso_repeated_perturbation_means_singular_,
prefix);
//Index pardiso_out_of_core_power;
//options.GetIntegerValue("pardiso_out_of_core_power",
// pardiso_out_of_core_power, prefix);
options.GetBoolValue("pardiso_skip_inertia_check",
skip_inertia_check_, prefix);
int pardiso_msglvl;
options.GetIntegerValue("pardiso_msglvl", pardiso_msglvl, prefix);
int max_iterref_steps;
options.GetIntegerValue("pardiso_max_iterative_refinement_steps", max_iterref_steps, prefix);
int order;
options.GetEnumValue("pardiso_order", order, prefix);
#if !defined(HAVE_PARDISO_OLDINTERFACE) && !defined(HAVE_PARDISO_MKL)
options.GetBoolValue("pardiso_iterative", pardiso_iterative_, prefix);
int pardiso_max_iter;
options.GetIntegerValue("pardiso_max_iter", pardiso_max_iter, prefix);
Number pardiso_iter_relative_tol;
options.GetNumericValue("pardiso_iter_relative_tol",
pardiso_iter_relative_tol, prefix);
Index pardiso_iter_coarse_size;
options.GetIntegerValue("pardiso_iter_coarse_size",
pardiso_iter_coarse_size, prefix);
Index pardiso_iter_max_levels;
options.GetIntegerValue("pardiso_iter_max_levels",
pardiso_iter_max_levels, prefix);
Number pardiso_iter_dropping_factor;
options.GetNumericValue("pardiso_iter_dropping_factor",
pardiso_iter_dropping_factor, prefix);
Number pardiso_iter_dropping_schur;
options.GetNumericValue("pardiso_iter_dropping_schur",
pardiso_iter_dropping_schur, prefix);
Index pardiso_iter_max_row_fill;
options.GetIntegerValue("pardiso_iter_max_row_fill",
pardiso_iter_max_row_fill, prefix);
Number pardiso_iter_inverse_norm_factor;
options.GetNumericValue("pardiso_iter_inverse_norm_factor",
pardiso_iter_inverse_norm_factor, prefix);
options.GetIntegerValue("pardiso_max_droptol_corrections",
pardiso_max_droptol_corrections_, prefix);
#else
pardiso_iterative_ = false;
#endif
// Number value = 0.0;
// Tell Pardiso to release all memory if it had been used before
if (initialized_) {
ipfint PHASE = -1;
ipfint N = dim_;
ipfint NRHS = 0;
ipfint ERROR;
ipfint idmy;
double ddmy;
PARDISO_FUNC(PT_, &MAXFCT_, &MNUM_, &MTYPE_, &PHASE, &N,
&ddmy, &idmy, &idmy, &idmy, &NRHS, IPARM_,
&MSGLVL_, &ddmy, &ddmy, &ERROR, DPARM_);
DBG_ASSERT(ERROR==0);
}
// Reset all private data
dim_=0;
nonzeros_=0;
have_symbolic_factorization_=false;
initialized_=false;
delete[] a_;
a_ = NULL;
#ifdef PARDISO_MATCHING_PREPROCESS
delete[] ia2;
ia2 = NULL;
delete[] ja2;
ja2 = NULL;
delete[] a2_;
a2_ = NULL;
delete[] perm2;
perm2 = NULL;
delete[] scale2;
scale2 = NULL;
#endif
// Call Pardiso's initialization routine
IPARM_[0] = 0; // Tell it to fill IPARM with default values(?)
#if ! defined(HAVE_PARDISO_OLDINTERFACE) && ! defined(HAVE_PARDISO_MKL)
ipfint ERROR = 0;
ipfint SOLVER = 0; // initialize only direct solver
PARDISOINIT_FUNC(PT_, &MTYPE_, &SOLVER, IPARM_, DPARM_, &ERROR);
#else
PARDISOINIT_FUNC(PT_, &MTYPE_, IPARM_);
#endif
// Set some parameters for Pardiso
IPARM_[0] = 1; // Don't use the default values
int num_procs = 1;
#if defined(HAVE_PARDISO_PARALLEL) || ! defined(HAVE_PARDISO)
// Obtain the numbers of processors from the value of OMP_NUM_THREADS
char* var = getenv("OMP_NUM_THREADS");
if (var != NULL) {
sscanf( var, "%d", &num_procs );
if (num_procs < 1) {
Jnlst().Printf(J_ERROR, J_LINEAR_ALGEBRA,
"Invalid value for OMP_NUM_THREADS (\"%s\").\n", var);
return false;
}
Jnlst().Printf(J_DETAILED, J_LINEAR_ALGEBRA,
"Using environment OMP_NUM_THREADS = %d as the number of processors for PARDISO.\n", num_procs);
}
#if defined(HAVE_PARDISO) && ! defined(HAVE_PARDISO_MKL)
// If we run Pardiso through the linear solver loader,
// we do not know whether it is the parallel version, so we do not report a warning if OMP_NUM_THREADS is not set.
// If we run Pardiso from MKL, then OMP_NUM_THREADS does not need to be set, so no warning.
else {
Jnlst().Printf(J_WARNING, J_LINEAR_ALGEBRA,
"You should set the environment variable OMP_NUM_THREADS to the number of processors used in Pardiso (e.g., 1).\n\n");
}
#endif
#endif
#ifdef HAVE_PARDISO_MKL
IPARM_[1] = order;
// For MKL PARDSIO, the documentation says, "iparm(3) Reserved. Set to zero.", so we don't set IPARM_[2]
IPARM_[5] = 1; // Overwrite right-hand side
IPARM_[7] = max_iterref_steps;
IPARM_[9] = 12; // pivot perturbation (as higher as less perturbation)
IPARM_[10] = 2; // enable scaling (recommended for interior-point indefinite matrices)
IPARM_[12] = (int)match_strat_; // enable matching (recommended, as above)
IPARM_[20] = 3; // bunch-kaufman pivoting
IPARM_[23] = 1; // parallel fac
IPARM_[24] = 1; // parallel solve
//IPARM_[26] = 1; // matrix checker
#else
IPARM_[1] = order;
IPARM_[2] = num_procs; // Set the number of processors
IPARM_[5] = 1; // Overwrite right-hand side
IPARM_[7] = max_iterref_steps;
// Options suggested by Olaf Schenk
IPARM_[9] = 12;
IPARM_[10] = 2; // Results in better scaling
// Matching information: IPARM_[12] = 1 seems ok, but results in a
// large number of pivot perturbation
// Matching information: IPARM_[12] = 2 robust, but more expensive method
IPARM_[12] = (int)match_strat_;
IPARM_[20] = 3; // Results in better accuracy
IPARM_[23] = 1; // parallel fac
IPARM_[24] = 1; // parallel solve
IPARM_[28] = 0; // 32-bit factorization
IPARM_[29] = 1; //we need this for IPOPT interface
//IPARM_[33] = 1; // bit-by-bit identical results in parallel run
#endif
Jnlst().Printf(J_DETAILED, J_LINEAR_ALGEBRA,
"Pardiso matrix ordering (IPARM(2)): %d\n", IPARM_[1]);
Jnlst().Printf(J_DETAILED, J_LINEAR_ALGEBRA,
"Pardiso max. iterref. steps (IPARM(8)): %d\n", IPARM_[7]);
Jnlst().Printf(J_DETAILED, J_LINEAR_ALGEBRA,
"Pardiso matching strategy (IPARM(13)): %d\n", IPARM_[12]);
if (pardiso_iterative_) {
#if defined(HAVE_PARDISO_OLDINTERFACE) || defined(HAVE_PARDISO_MKL)
THROW_EXCEPTION(OPTION_INVALID,
"You chose to use the iterative version of Pardiso, but you need to use a Pardiso version of at least 4.0.");
#else
IPARM_[31] = 1 ; // active direct solver
DPARM_[ 0] = pardiso_max_iter; // maximum number of Krylov-Subspace Iteration
// Default is 300
// 1 <= value <= e.g. 1000
DPARM_[ 1] = pardiso_iter_relative_tol; // Relative Residual Convergence
// e.g. pardiso_iter_tol
// Default is 1e-6
// 1e-16 <= value < 1
DPARM_[ 2] = pardiso_iter_coarse_size; // Maximum Size of Coarse Grid Matrix
// e.g. pardiso_coarse_grid
// Default is 5000
// 1 <= value < number of equations
DPARM_[ 3] = pardiso_iter_max_levels; // Maximum Number of Grid Levels
// e.g. pardiso_max_grid
// Default is 10000
// 1 <= value < number of equations
DPARM_[ 4] = pardiso_iter_dropping_factor; // dropping value for incomplete factor
// e.g. pardiso_dropping_factor
// Default is 0.5
// 1e-16 <= value < 1
DPARM_[ 5] = pardiso_iter_dropping_schur; // dropping value for sparsify schur complementfactor
// e.g. pardiso_dropping_schur
// Default is 0.1
// 1e-16 <= value < 1
DPARM_[ 6] = pardiso_iter_max_row_fill; // max fill for each row
// e.g. pardiso_max_fill
// Default is 1000
// 1 <= value < 100000
DPARM_[ 7] = pardiso_iter_inverse_norm_factor; // dropping value for sparsify schur complementfactor
// e.g. pardiso_inverse_norm_factor
// Default is 500
// 2 <= value < 50000
DPARM_[ 8] = 25; // maximum number of non-improvement steps
#endif
}
MSGLVL_ = pardiso_msglvl;
// Option for the out of core variant
//IPARM_[49] = pardiso_out_of_core_power;
return true;
}
SmartPtr<MuUpdate> AlgorithmBuilder::BuildMuUpdate(
const Journalist& jnlst,
const OptionsList& options,
const std::string& prefix
)
{
DBG_ASSERT(IsValid(LineSearch_));
bool mehrotra_algorithm;
options.GetBoolValue("mehrotra_algorithm", mehrotra_algorithm, prefix);
// Create the mu update that will be used by the main algorithm
SmartPtr<MuUpdate> MuUpdate;
std::string smuupdate;
if( !options.GetStringValue("mu_strategy", smuupdate, prefix) )
{
// Change default for quasi-Newton option (then we use adaptive)
Index enum_int;
if( options.GetEnumValue("hessian_approximation", enum_int, prefix) )
{
HessianApproximationType hessian_approximation = HessianApproximationType(enum_int);
if( hessian_approximation == LIMITED_MEMORY )
{
smuupdate = "adaptive";
}
}
if( mehrotra_algorithm )
{
smuupdate = "adaptive";
}
}
ASSERT_EXCEPTION(!mehrotra_algorithm || smuupdate == "adaptive", OPTION_INVALID,
"If mehrotra_algorithm=yes, mu_strategy must be \"adaptive\".");
std::string smuoracle;
std::string sfixmuoracle;
if( smuupdate == "adaptive" )
{
if( !options.GetStringValue("mu_oracle", smuoracle, prefix) )
{
if( mehrotra_algorithm )
{
smuoracle = "probing";
}
}
options.GetStringValue("fixed_mu_oracle", sfixmuoracle, prefix);
ASSERT_EXCEPTION(!mehrotra_algorithm || smuoracle == "probing", OPTION_INVALID,
"If mehrotra_algorithm=yes, mu_oracle must be \"probing\".");
}
if( smuupdate == "monotone" )
{
MuUpdate = new MonotoneMuUpdate(GetRawPtr(LineSearch_));
}
else if( smuupdate == "adaptive" )
{
SmartPtr<MuOracle> muOracle;
if( smuoracle == "loqo" )
{
muOracle = new LoqoMuOracle();
}
else if( smuoracle == "probing" )
{
muOracle = new ProbingMuOracle(GetPDSystemSolver(jnlst, options, prefix));
}
else if( smuoracle == "quality-function" )
{
muOracle = new QualityFunctionMuOracle(GetPDSystemSolver(jnlst, options, prefix));
}
SmartPtr<MuOracle> FixMuOracle;
if( sfixmuoracle == "loqo" )
{
FixMuOracle = new LoqoMuOracle();
}
else if( sfixmuoracle == "probing" )
{
FixMuOracle = new ProbingMuOracle(GetPDSystemSolver(jnlst, options, prefix));
}
else if( sfixmuoracle == "quality-function" )
{
FixMuOracle = new QualityFunctionMuOracle(GetPDSystemSolver(jnlst, options, prefix));
}
else
{
FixMuOracle = NULL;
}
MuUpdate = new AdaptiveMuUpdate(GetRawPtr(LineSearch_), muOracle, FixMuOracle);
}
return MuUpdate;
}
SmartPtr<LineSearch> AlgorithmBuilder::BuildLineSearch(
const Journalist& jnlst,
const OptionsList& options,
const std::string& prefix
)
{
DBG_ASSERT(IsValid(ConvCheck_));
DBG_ASSERT(IsValid(EqMultCalculator_));
Index enum_int;
options.GetEnumValue("hessian_approximation", enum_int, prefix);
HessianApproximationType hessian_approximation = HessianApproximationType(enum_int);
SmartPtr<RestorationPhase> resto_phase;
SmartPtr<RestoConvergenceCheck> resto_convCheck;
// We only need a restoration phase object if we use the filter
// line search
std::string lsmethod;
options.GetStringValue("line_search_method", lsmethod, prefix);
if( lsmethod == "filter" || lsmethod == "penalty" )
{
// Solver for the restoration phase
SmartPtr<AugSystemSolver> resto_AugSolver = new AugRestoSystemSolver(*GetAugSystemSolver(jnlst, options, prefix));
SmartPtr<PDPerturbationHandler> resto_pertHandler = new PDPerturbationHandler();
SmartPtr<PDSystemSolver> resto_PDSolver = new PDFullSpaceSolver(*resto_AugSolver, *resto_pertHandler);
// Convergence check in the restoration phase
if( lsmethod == "filter" )
{
resto_convCheck = new RestoFilterConvergenceCheck();
}
else if( lsmethod == "penalty" )
{
resto_convCheck = new RestoPenaltyConvergenceCheck();
}
// Line search method for the restoration phase
SmartPtr<RestoRestorationPhase> resto_resto = new RestoRestorationPhase();
SmartPtr<BacktrackingLSAcceptor> resto_LSacceptor;
std::string resto_lsacceptor;
options.GetStringValue("line_search_method", resto_lsacceptor, "resto." + prefix);
if( resto_lsacceptor == "filter" )
{
resto_LSacceptor = new FilterLSAcceptor(GetRawPtr(resto_PDSolver));
}
else if( resto_lsacceptor == "cg-penalty" )
{
resto_LSacceptor = new CGPenaltyLSAcceptor(GetRawPtr(resto_PDSolver));
}
else if( resto_lsacceptor == "penalty" )
{
resto_LSacceptor = new PenaltyLSAcceptor(GetRawPtr(resto_PDSolver));
}
SmartPtr<LineSearch> resto_LineSearch = new BacktrackingLineSearch(resto_LSacceptor, GetRawPtr(resto_resto),
GetRawPtr(resto_convCheck));
// Create the mu update that will be used by the restoration phase
// algorithm
SmartPtr<MuUpdate> resto_MuUpdate;
std::string resto_smuupdate;
if( !options.GetStringValue("mu_strategy", resto_smuupdate, "resto." + prefix) )
{
// Change default for quasi-Newton option (then we use adaptive)
if( hessian_approximation == LIMITED_MEMORY )
{
resto_smuupdate = "adaptive";
}
}
std::string resto_smuoracle;
std::string resto_sfixmuoracle;
if( resto_smuupdate == "adaptive" )
{
options.GetStringValue("mu_oracle", resto_smuoracle, "resto." + prefix);
options.GetStringValue("fixed_mu_oracle", resto_sfixmuoracle, "resto." + prefix);
}
if( resto_smuupdate == "monotone" )
{
resto_MuUpdate = new MonotoneMuUpdate(GetRawPtr(resto_LineSearch));
}
else if( resto_smuupdate == "adaptive" )
{
SmartPtr<MuOracle> resto_MuOracle;
if( resto_smuoracle == "loqo" )
{
resto_MuOracle = new LoqoMuOracle();
}
else if( resto_smuoracle == "probing" )
{
resto_MuOracle = new ProbingMuOracle(resto_PDSolver);
}
else if( resto_smuoracle == "quality-function" )
{
resto_MuOracle = new QualityFunctionMuOracle(resto_PDSolver);
}
SmartPtr<MuOracle> resto_FixMuOracle;
if( resto_sfixmuoracle == "loqo" )
{
resto_FixMuOracle = new LoqoMuOracle();
}
else if( resto_sfixmuoracle == "probing" )
{
resto_FixMuOracle = new ProbingMuOracle(resto_PDSolver);
}
else if( resto_sfixmuoracle == "quality-function" )
{
resto_FixMuOracle = new QualityFunctionMuOracle(resto_PDSolver);
}
else
{
resto_FixMuOracle = NULL;
}
resto_MuUpdate = new AdaptiveMuUpdate(GetRawPtr(resto_LineSearch), resto_MuOracle, resto_FixMuOracle);
}
// Initialization of the iterates for the restoration phase
SmartPtr<EqMultiplierCalculator> resto_EqMultCalculator = new LeastSquareMultipliers(*resto_AugSolver);
SmartPtr<IterateInitializer> resto_IterInitializer = new RestoIterateInitializer(resto_EqMultCalculator);
// Create the object for the iteration output during restoration
SmartPtr<OrigIterationOutput> resto_OrigIterOutput = NULL;
// new OrigIterationOutput();
SmartPtr<IterationOutput> resto_IterOutput = new RestoIterationOutput(resto_OrigIterOutput);
// Get the Hessian updater for the restoration phase
SmartPtr<HessianUpdater> resto_HessUpdater;
switch( hessian_approximation )
{
case EXACT:
resto_HessUpdater = new ExactHessianUpdater();
break;
case LIMITED_MEMORY:
// ToDo This needs to be replaced!
resto_HessUpdater = new LimMemQuasiNewtonUpdater(true);
break;
}
// Put together the overall restoration phase IP algorithm
SmartPtr<SearchDirectionCalculator> resto_SearchDirCalc;
if( resto_lsacceptor == "cg-penalty" )
{
resto_SearchDirCalc = new CGSearchDirCalculator(GetRawPtr(resto_PDSolver));
}
else
{
resto_SearchDirCalc = new PDSearchDirCalculator(GetRawPtr(resto_PDSolver));
}
SmartPtr<IpoptAlgorithm> resto_alg = new IpoptAlgorithm(resto_SearchDirCalc, GetRawPtr(resto_LineSearch),
GetRawPtr(resto_MuUpdate), GetRawPtr(resto_convCheck), resto_IterInitializer, resto_IterOutput,
resto_HessUpdater, resto_EqMultCalculator);
// Set the restoration phase
resto_phase = new MinC_1NrmRestorationPhase(*resto_alg, EqMultCalculator_);
}
// Create the line search to be used by the main algorithm
SmartPtr<BacktrackingLSAcceptor> LSacceptor;
if( lsmethod == "filter" )
{
LSacceptor = new FilterLSAcceptor(GetRawPtr(GetPDSystemSolver(jnlst, options, prefix)));
}
else if( lsmethod == "cg-penalty" )
{
LSacceptor = new CGPenaltyLSAcceptor(GetRawPtr(GetPDSystemSolver(jnlst, options, prefix)));
}
else if( lsmethod == "penalty" )
{
LSacceptor = new PenaltyLSAcceptor(GetRawPtr(GetPDSystemSolver(jnlst, options, prefix)));
}
SmartPtr<LineSearch> LineSearch = new BacktrackingLineSearch(LSacceptor, GetRawPtr(resto_phase), ConvCheck_);
// The following cross reference is not good: We have to store a
// pointer to the LineSearch_ object in resto_convCheck as a
// non-SmartPtr to make sure that things are properly deleted when
// the IpoptAlgorithm returned by the Builder is destructed.
if( IsValid(resto_convCheck) )
{
resto_convCheck->SetOrigLSAcceptor(*LSacceptor);
}
return LineSearch;
}
