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 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;
}
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;
}
bool IpoptAlgorithm::InitializeImpl(const OptionsList& options,
const std::string& prefix)
{
DBG_START_METH("IpoptAlgorithm::InitializeImpl",
dbg_verbosity);
SmartPtr<const OptionsList> my_options;
options.GetBoolValue("mehrotra_algorithm", mehrotra_algorithm_, prefix);
if (mehrotra_algorithm_) {
// Verify a few options and set a few new ones. But we better
// make a copy of the incoming options.
SmartPtr<OptionsList> new_options = new OptionsList(options);
// Check required options are set correctly
std::string string_option;
if (new_options->GetStringValue("adaptive_mu_globalization", string_option, prefix)) {
ASSERT_EXCEPTION(string_option=="never-monotone-mode", OPTION_INVALID,
"If mehrotra_algorithm=yes, adaptive_mu_globalization must be \"never-monotone-mode\".");
}
else {
new_options->SetStringValue("adaptive_mu_globalization",
"never-monotone-mode", false);
}
// The corrector step is already taken case of in
// ComputeSearchDirection below
if (new_options->GetStringValue("corrector_type", string_option, prefix)) {
ASSERT_EXCEPTION(string_option=="none", OPTION_INVALID,
"If mehrotra_algorithm=yes, corrector_type must be \"none\".");
}
else {
new_options->SetStringValue("corrector_type", "none", false);
}
if (new_options->GetStringValue("accept_every_trial_step", string_option, prefix)) {
ASSERT_EXCEPTION(string_option=="yes", OPTION_INVALID,
"If mehrotra_algorithm=yes, accept_every_trial_step must be \"yes\".");
}
else {
new_options->SetStringValue("accept_every_trial_step", "yes", false);
}
// Change some default options
new_options->SetNumericValueIfUnset("bound_push", 10.);
new_options->SetNumericValueIfUnset("bound_frac", 0.2);
new_options->SetNumericValueIfUnset("bound_mult_init_val", 10.);
new_options->SetNumericValueIfUnset("constr_mult_init_max", 0.);
new_options->SetStringValueIfUnset("alpha_for_y", "bound_mult");
new_options->SetStringValueIfUnset("least_square_init_primal", "yes");
my_options = ConstPtr(new_options);
}
else {
my_options = &options;
}
bool bval;
options.GetBoolValue("sb", bval, prefix);
if (bval) {
copyright_message_printed = true;
}
// Store which linear solver is chosen for later output
options.GetStringValue("linear_solver", linear_solver_, prefix);
// Read the IpoptAlgorithm options
// Initialize the Data object
bool retvalue = IpData().Initialize(Jnlst(), *my_options, prefix);
ASSERT_EXCEPTION(retvalue, FAILED_INITIALIZATION,
"the IpIpoptData object failed to initialize.");
// Initialize the CQ object
retvalue = IpCq().Initialize(Jnlst(), *my_options, prefix);
ASSERT_EXCEPTION(retvalue, FAILED_INITIALIZATION,
"the IpIpoptCalculatedQuantities object failed to initialize.");
// Initialize the NLP object
retvalue = IpNLP().Initialize(Jnlst(), *my_options, prefix);
ASSERT_EXCEPTION(retvalue, FAILED_INITIALIZATION,
"the IpIpoptNLP object failed to initialize.");
// Initialize all the strategies
retvalue = iterate_initializer_->Initialize(Jnlst(), IpNLP(), IpData(),
IpCq(), *my_options, prefix);
ASSERT_EXCEPTION(retvalue, FAILED_INITIALIZATION,
"the iterate_initializer strategy failed to initialize.");
retvalue = mu_update_->Initialize(Jnlst(), IpNLP(), IpData(), IpCq(),
*my_options, prefix);
ASSERT_EXCEPTION(retvalue, FAILED_INITIALIZATION,
"the mu_update strategy failed to initialize.");
retvalue = search_dir_calculator_->Initialize(Jnlst(), IpNLP(), IpData(), IpCq(),
options,prefix);
ASSERT_EXCEPTION(retvalue, FAILED_INITIALIZATION,
"the search_direction_calculator strategy failed to initialize.");
retvalue = line_search_->Initialize(Jnlst(), IpNLP(), IpData(), IpCq(),
*my_options,prefix);
ASSERT_EXCEPTION(retvalue, FAILED_INITIALIZATION,
"the line_search strategy failed to initialize.");
retvalue = conv_check_->Initialize(Jnlst(), IpNLP(), IpData(), IpCq(),
*my_options, prefix);
ASSERT_EXCEPTION(retvalue, FAILED_INITIALIZATION,
"the conv_check strategy failed to initialize.");
retvalue = iter_output_->Initialize(Jnlst(), IpNLP(), IpData(), IpCq(),
*my_options, prefix);
ASSERT_EXCEPTION(retvalue, FAILED_INITIALIZATION,
"the iter_output strategy failed to initialize.");
retvalue = hessian_updater_->Initialize(Jnlst(), IpNLP(), IpData(), IpCq(),
*my_options, prefix);
ASSERT_EXCEPTION(retvalue, FAILED_INITIALIZATION,
"the hessian_updater strategy failed to initialize.");
my_options->GetNumericValue("kappa_sigma", kappa_sigma_, prefix);
if (!my_options->GetBoolValue("recalc_y", recalc_y_, prefix)) {
Index enum_int;
if (my_options->GetEnumValue("hessian_approximation", enum_int, prefix)) {
HessianApproximationType hessian_approximation =
HessianApproximationType(enum_int);
if (hessian_approximation==LIMITED_MEMORY) {
recalc_y_ = true;
}
}
}
if (recalc_y_) {
my_options->GetNumericValue("recalc_y_feas_tol", recalc_y_feas_tol_,
prefix);
}
if (prefix=="resto.") {
skip_print_problem_stats_ = true;
}
else {
skip_print_problem_stats_ = false;
}
return true;
}
