44 #ifndef ROL_TRUSTREGION_H 45 #define ROL_TRUSTREGION_H 88 : ftol_old_(
ROL_OVERFLOW<Real>()), cnt_(0), verbosity_(0) {
90 ROL::ParameterList list = parlist.sublist(
"Step").sublist(
"Trust Region");
92 eta0_ = list.get(
"Step Acceptance Threshold", static_cast<Real>(0.05));
93 eta1_ = list.get(
"Radius Shrinking Threshold", static_cast<Real>(0.05));
94 eta2_ = list.get(
"Radius Growing Threshold", static_cast<Real>(0.9));
95 gamma0_ = list.get(
"Radius Shrinking Rate (Negative rho)", static_cast<Real>(0.0625));
96 gamma1_ = list.get(
"Radius Shrinking Rate (Positive rho)", static_cast<Real>(0.25));
97 gamma2_ = list.get(
"Radius Growing Rate", static_cast<Real>(2.5));
98 mu0_ = list.get(
"Sufficient Decrease Parameter", static_cast<Real>(1.e-4));
99 TRsafe_ = list.get(
"Safeguard Size", static_cast<Real>(100.0));
100 eps_ = TRsafe_*ROL_EPSILON<Real>();
102 ROL::ParameterList &glist = parlist.sublist(
"General");
104 useInexact_.push_back(glist.get(
"Inexact Objective Function",
false));
105 useInexact_.push_back(glist.get(
"Inexact Gradient",
false));
106 useInexact_.push_back(glist.get(
"Inexact Hessian-Times-A-Vector",
false));
108 ROL::ParameterList &ilist = list.sublist(
"Inexact").sublist(
"Value");
109 scale_ = ilist.get(
"Tolerance Scaling", static_cast<Real>(1.e-1));
110 omega_ = ilist.get(
"Exponent", static_cast<Real>(0.9));
111 force_ = ilist.get(
"Forcing Sequence Initial Value", static_cast<Real>(1.0));
112 updateIter_ = ilist.get(
"Forcing Sequence Update Frequency", static_cast<int>(10));
113 forceFactor_ = ilist.get(
"Forcing Sequence Reduction Factor", static_cast<Real>(0.1));
115 verbosity_ = glist.get(
"Print Verbosity", 0);
137 Real tol = std::sqrt(ROL_EPSILON<Real>());
138 const Real one(1),
zero(0);
144 Real fold1 = fold, ftol = tol;
145 if ( useInexact_[0] ) {
146 if ( !(cnt_%updateIter_) && (cnt_ != 0) ) {
158 Real eta =
static_cast<Real
>(0.999)*std::min(eta1_,one-eta2_);
159 ftol = scale_*std::pow(eta*std::min(pRed_,force_),one/omega_);
161 fold1 = obj.
value(x,ftol_old_);
165 prim_->set(x); prim_->plus(s);
167 fnew = obj.
value(*prim_,ftol);
170 Real aRed = fold1 - fnew;
182 if ( verbosity_ > 0 ) {
183 std::cout << std::endl;
184 std::cout <<
" Computation of actual and predicted reduction" << std::endl;
185 std::cout <<
" Current objective function value: " << fold1 << std::endl;
186 std::cout <<
" New objective function value: " << fnew << std::endl;
187 std::cout <<
" Actual reduction: " << aRed << std::endl;
188 std::cout <<
" Predicted reduction: " << pRed_ << std::endl;
192 Real EPS = eps_*((one > std::abs(fold1)) ? one : std::abs(fold1));
193 Real aRed_safe = aRed + EPS, pRed_safe = pRed_ + EPS;
195 if (((std::abs(aRed_safe) < eps_) && (std::abs(pRed_safe) < eps_)) || aRed == pRed_) {
199 else if ( std::isnan(aRed_safe) || std::isnan(pRed_safe) ) {
204 rho = aRed_safe/pRed_safe;
205 if (pRed_safe < zero && aRed_safe > zero) {
208 else if (aRed_safe <= zero && pRed_safe > zero) {
211 else if (aRed_safe <= zero && pRed_safe < zero) {
219 if ( verbosity_ > 0 ) {
220 std::cout <<
" Safeguard: " << eps_ << std::endl;
221 std::cout <<
" Actual reduction with safeguard: " << aRed_safe << std::endl;
222 std::cout <<
" Predicted reduction with safeguard: " << pRed_safe << std::endl;
223 std::cout <<
" Ratio of actual and predicted reduction: " << rho << std::endl;
224 std::cout <<
" Trust-region flag: " << flagTR << std::endl;
236 if ( rho >= eta0_ && (std::abs(aRed_safe) > eps_) ) {
239 prim_->axpy(-one,g.
dual());
243 Real pgnorm = prim_->norm();
245 prim_->set(g.
dual());
247 Real lam = std::min(one, del/prim_->norm());
253 pgnorm *= prim_->norm();
255 decr = ( aRed_safe >= mu0_*pgnorm );
258 if ( verbosity_ > 0 ) {
259 std::cout <<
" Decrease lower bound (constraints): " << mu0_*pgnorm << std::endl;
260 std::cout <<
" Trust-region flag (constraints): " << flagTR << std::endl;
261 std::cout <<
" Is step feasible: " << bnd.
isFeasible(x) << std::endl;
272 if ( verbosity_ > 0 ) {
273 std::cout <<
" Norm of step: " << snorm << std::endl;
274 std::cout <<
" Trust-region radius before update: " << del << std::endl;
282 gs = dual_->dot(s.
dual());
287 Real modelVal = model.
value(s,tol);
289 Real theta = (one-
eta2_)*gs/((one-eta2_)*(fold1+gs)+eta2_*modelVal-fnew);
290 del = std::min(gamma1_*std::min(snorm,del),std::max(gamma0_,theta)*del);
291 if ( verbosity_ > 0 ) {
292 std::cout <<
" Interpolation model value: " << modelVal << std::endl;
293 std::cout <<
" Interpolation step length: " << theta << std::endl;
297 del = gamma1_*std::min(snorm,del);
309 if ( verbosity_ > 0 ) {
310 std::cout <<
" Trust-region radius after update: " << del << std::endl;
311 std::cout << std::endl;
virtual const Ptr< const Vector< Real > > getGradient(void) const
Provides the interface to evaluate objective functions.
virtual ROL::Ptr< Vector > clone() const =0
Clone to make a new (uninitialized) vector.
virtual void plus(const Vector &x)=0
Compute , where .
virtual Real value(const Vector< Real > &x, Real &tol)=0
Compute value.
virtual void initialize(const Vector< Real > &x, const Vector< Real > &s, const Vector< Real > &g)
Contains definitions of custom data types in ROL.
bool isActivated(void) const
Check if bounds are on.
Provides interface for and implements trust-region subproblem solvers.
void pruneActive(Vector< Real > &v, const Vector< Real > &x, Real eps=0)
Set variables to zero if they correspond to the -active set.
Provides the interface to evaluate trust-region model functions.
Defines the linear algebra or vector space interface.
virtual void updatePredictedReduction(Real &pred, const Vector< Real > &s)
virtual Real dot(const Vector &x) const =0
Compute where .
Objective_SerialSimOpt(const Ptr< Obj > &obj, const V &ui) z0_ zero()
virtual void dualTransform(Vector< Real > &tv, const Vector< Real > &v)
virtual const Vector & dual() const
Return dual representation of , for example, the result of applying a Riesz map, or change of basis...
ETrustRegionModel StringToETrustRegionModel(std::string s)
Real getPredictedReduction(void) const
virtual Real value(const Vector< Real > &s, Real &tol)
Compute value.
void setPredictedReduction(const Real pRed)
Real ROL_OVERFLOW(void)
Platform-dependent maximum double.
ETrustRegionModel
Enumeration of trust-region model types.
TrustRegion(ROL::ParameterList &parlist)
Provides the interface to apply upper and lower bound constraints.
virtual void updateActualReduction(Real &ared, const Vector< Real > &s)
virtual void update(const Vector< Real > &x, bool flag=true, int iter=-1)
Update objective function.
ETrustRegionFlag
Enumation of flags used by trust-region solvers.
ETrustRegionModel TRmodel_
ROL::Ptr< Vector< Real > > dual_
virtual bool isFeasible(const Vector< Real > &v)
Check if the vector, v, is feasible.
Contains definitions of enums for trust region algorithms.
std::vector< bool > useInexact_
virtual void project(Vector< Real > &x)
Project optimization variables onto the bounds.
virtual void run(Vector< Real > &s, Real &snorm, int &iflag, int &iter, const Real del, TrustRegionModel< Real > &model)=0
virtual void update(Vector< Real > &x, Real &fnew, Real &del, int &nfval, int &ngrad, ETrustRegionFlag &flagTR, const Vector< Real > &s, const Real snorm, const Real fold, const Vector< Real > &g, int iter, Objective< Real > &obj, BoundConstraint< Real > &bnd, TrustRegionModel< Real > &model)
ROL::Ptr< Vector< Real > > prim_