44 #ifndef ROL_TYPEG_MOREAUYOSIDAALGORITHM_DEF_H
45 #define ROL_TYPEG_MOREAUYOSIDAALGORITHM_DEF_H
52 template<
typename Real>
55 tau_(10), print_(false), list_(list), subproblemIter_(0) {
61 Real ten(10), oem6(1.e-6), oem8(1.e-8), oe8(1e8);
62 ParameterList& steplist = list.sublist(
"Step").sublist(
"Moreau-Yosida Penalty");
63 state_->searchSize = steplist.get(
"Initial Penalty Parameter", ten);
64 maxPenalty_ = steplist.get(
"Maximum Penalty Parameter", oe8);
65 tau_ = steplist.get(
"Penalty Parameter Growth Factor", ten);
68 print_ = steplist.sublist(
"Subproblem").get(
"Print History",
false);
70 Real gtol = steplist.sublist(
"Subproblem").get(
"Optimality Tolerance", oem8);
71 Real ctol = steplist.sublist(
"Subproblem").get(
"Feasibility Tolerance", oem8);
72 int maxit = steplist.sublist(
"Subproblem").get(
"Iteration Limit", 1000);
73 bool reltol = steplist.sublist(
"Subproblem").get(
"Use Relative Tolerances",
true);
74 Real stol = oem6*std::min(gtol,ctol);
75 list_.sublist(
"Status Test").set(
"Gradient Tolerance", gtol);
76 list_.sublist(
"Status Test").set(
"Constraint Tolerance", ctol);
77 list_.sublist(
"Status Test").set(
"Step Tolerance", stol);
78 list_.sublist(
"Status Test").set(
"Iteration Limit", maxit);
79 list_.sublist(
"Status Test").set(
"Use Relative Tolerances", reltol);
81 stepname_ = steplist.sublist(
"Subproblem").get(
"Step Type",
"Augmented Lagrangian");
85 verbosity_ = list.sublist(
"General").get(
"Output Level", 0);
91 template<
typename Real>
101 std::ostream &outStream) {
103 if (proj_ == nullPtr) {
104 proj_ = makePtr<PolyhedralProjection<Real>>(makePtrFromRef(bnd));
105 hasPolyProj_ =
false;
107 proj_->project(x,outStream);
114 updateState(x,l,myobj,bnd,con,pwa,dwa,outStream);
118 template<
typename Real>
126 std::ostream &outStream) {
128 Real zerotol = std::sqrt(ROL_EPSILON<Real>());
130 if (state_->iter == 0) {
143 state_->gradientVec->plus(dwa);
146 pwa.
axpy(-one,state_->gradientVec->dual());
147 proj_->project(pwa,outStream);
151 con.
value(*state_->constraintVec, x, zerotol);
152 state_->cnorm = state_->constraintVec->norm();
154 state_->gnorm = std::max(gnorm_,compViolation_);
161 template<
typename Real>
169 std::ostream &outStream ) {
171 Ptr<Vector<Real>> pwa = x.
clone(), dwa = g.
clone();
174 x,g,state_->searchSize,updateMultiplier_,
176 initialize(x,g,emul,eres,myobj,bnd,econ,*pwa,*dwa,outStream);
177 Ptr<TypeE::Algorithm<Real>> algo;
180 if (verbosity_ > 0) writeOutput(outStream,
true);
182 while (status_->check(*state_)) {
184 algo = TypeE::AlgorithmFactory<Real>(list_,secant_);
186 if (hasPolyProj_) algo->run(x,g,myobj,econ,emul,eres,
187 *proj_->getLinearConstraint(),
188 *proj_->getMultiplier(),
189 *proj_->getResidual(),outStream);
190 else algo->run(x,g,myobj,econ,emul,eres,outStream);
191 subproblemIter_ = algo->getState()->iter;
192 state_->nfval += algo->getState()->nfval;
193 state_->ngrad += algo->getState()->ngrad;
194 state_->ncval += algo->getState()->ncval;
197 state_->stepVec->set(x);
198 state_->stepVec->axpy(-one,*state_->iterateVec);
199 state_->snorm = state_->stepVec->norm();
200 state_->lagmultVec->axpy(-one,emul);
201 state_->snorm += state_->lagmultVec->norm();
204 state_->iterateVec->set(x);
205 state_->lagmultVec->set(emul);
211 updateState(x,emul,myobj,bnd,econ,*pwa,*dwa);
215 state_->searchSize = std::min(tau_*state_->searchSize,maxPenalty_);
219 if (verbosity_ > 0) writeOutput(outStream,printHeader_);
224 template<
typename Real>
226 std::ios_base::fmtflags osFlags(os.flags());
227 if (verbosity_ > 1) {
228 os << std::string(109,
'-') << std::endl;
229 os <<
"Moreau-Yosida Penalty Solver";
230 os <<
" status output definitions" << std::endl << std::endl;
231 os <<
" iter - Number of iterates (steps taken)" << std::endl;
232 os <<
" fval - Objective function value" << std::endl;
233 os <<
" cnorm - Norm of the constraint" << std::endl;
234 os <<
" gLnorm - Norm of the gradient of the Lagrangian" << std::endl;
235 os <<
" ifeas - Infeasibility metric" << std::endl;
236 os <<
" snorm - Norm of the step (update to optimization vector)" << std::endl;
237 os <<
" penalty - Penalty parameter for bound constraints" << std::endl;
238 os <<
" #fval - Cumulative number of times the objective function was evaluated" << std::endl;
239 os <<
" #grad - Cumulative number of times the gradient was computed" << std::endl;
240 os <<
" #cval - Cumulative number of times the constraint was evaluated" << std::endl;
241 os <<
" subiter - Number of subproblem iterations" << std::endl;
242 os << std::string(109,
'-') << std::endl;
246 os << std::setw(6) << std::left <<
"iter";
247 os << std::setw(15) << std::left <<
"fval";
248 os << std::setw(15) << std::left <<
"cnorm";
249 os << std::setw(15) << std::left <<
"gLnorm";
250 os << std::setw(15) << std::left <<
"ifeas";
251 os << std::setw(15) << std::left <<
"snorm";
252 os << std::setw(10) << std::left <<
"penalty";
253 os << std::setw(8) << std::left <<
"#fval";
254 os << std::setw(8) << std::left <<
"#grad";
255 os << std::setw(8) << std::left <<
"#cval";
256 os << std::setw(8) << std::left <<
"subIter";
261 template<
typename Real>
263 std::ios_base::fmtflags osFlags(os.flags());
264 os << std::endl <<
"Moreau-Yosida Penalty Solver (Type G, General Constraints)";
266 os <<
"Subproblem Solver: " << stepname_ << std::endl;
270 template<
typename Real>
272 std::ios_base::fmtflags osFlags(os.flags());
273 os << std::scientific << std::setprecision(6);
274 if ( state_->iter == 0 ) writeName(os);
275 if ( print_header ) writeHeader(os);
276 if ( state_->iter == 0 ) {
278 os << std::setw(6) << std::left << state_->iter;
279 os << std::setw(15) << std::left << state_->value;
280 os << std::setw(15) << std::left << state_->cnorm;
281 os << std::setw(15) << std::left << gnorm_;
282 os << std::setw(15) << std::left << compViolation_;
283 os << std::setw(15) << std::left <<
"---";
284 os << std::scientific << std::setprecision(2);
285 os << std::setw(10) << std::left << state_->searchSize;
286 os << std::setw(8) << std::left << state_->nfval;
287 os << std::setw(8) << std::left << state_->ngrad;
288 os << std::setw(8) << std::left << state_->ncval;
289 os << std::setw(8) << std::left <<
"---";
294 os << std::setw(6) << std::left << state_->iter;
295 os << std::setw(15) << std::left << state_->value;
296 os << std::setw(15) << std::left << state_->cnorm;
297 os << std::setw(15) << std::left << gnorm_;
298 os << std::setw(15) << std::left << compViolation_;
299 os << std::setw(15) << std::left << state_->snorm;
300 os << std::scientific << std::setprecision(2);
301 os << std::setw(10) << std::left << state_->searchSize;
302 os << std::scientific << std::setprecision(6);
303 os << std::setw(8) << std::left << state_->nfval;
304 os << std::setw(8) << std::left << state_->ngrad;
305 os << std::setw(8) << std::left << state_->ncval;
306 os << std::setw(8) << std::left << subproblemIter_;
void updateState(const Vector< Real > &x, const Vector< Real > &l, MoreauYosidaObjective< Real > &myobj, BoundConstraint< Real > &bnd, Constraint< Real > &con, Vector< Real > &pwa, Vector< Real > &dwa, std::ostream &outStream=std::cout)
Provides the interface to evaluate objective functions.
virtual ROL::Ptr< Vector > clone() const =0
Clone to make a new (uninitialized) vector.
virtual void update(const Vector< Real > &x, UpdateType type, int iter=-1)
Update constraint function.
virtual void axpy(const Real alpha, const Vector &x)
Compute where .
Real getObjectiveValue(const Vector< Real > &x, Real &tol)
void writeHeader(std::ostream &os) const override
Print iterate header.
virtual void writeExitStatus(std::ostream &os) const
void writeName(std::ostream &os) const override
Print step name.
virtual void zero()
Set to zero vector.
Defines the linear algebra or vector space interface.
virtual void value(Vector< Real > &c, const Vector< Real > &x, Real &tol)=0
Evaluate the constraint operator at .
void updateMultipliers(Real mu, const Vector< Real > &x)
Provides an interface to check status of optimization algorithms for problems with equality constrain...
Provides an interface to run general constrained optimization algorithms.
void initialize(Vector< Real > &x, const Vector< Real > &g, const Vector< Real > &l, const Vector< Real > &c, MoreauYosidaObjective< Real > &myobj, BoundConstraint< Real > &bnd, Constraint< Real > &con, Vector< Real > &pwa, Vector< Real > &dwa, std::ostream &outStream=std::cout)
void update(const Vector< Real > &x, UpdateType type, int iter=-1)
Update Moreau-Yosida penalty function.
const Ptr< AlgorithmState< Real > > state_
Provides the interface to evaluate the Moreau-Yosida penalty function.
Provides interface for and implements limited-memory secant operators.
void writeOutput(std::ostream &os, const bool print_header=false) const override
Print iterate status.
void run(Vector< Real > &x, const Vector< Real > &g, Objective< Real > &obj, BoundConstraint< Real > &bnd, Constraint< Real > &econ, Vector< Real > &emul, const Vector< Real > &eres, std::ostream &outStream=std::cout) override
Run algorithm on general constrained problems (Type-G). This is the primary Type-G interface...
Provides the interface to apply upper and lower bound constraints.
virtual void applyAdjointJacobian(Vector< Real > &ajv, const Vector< Real > &v, const Vector< Real > &x, Real &tol)
Apply the adjoint of the the constraint Jacobian at , , to vector .
MoreauYosidaAlgorithm(ParameterList &list, const Ptr< Secant< Real >> &secant=nullPtr)
virtual void set(const Vector &x)
Set where .
void getObjectiveGradient(Vector< Real > &g, const Vector< Real > &x, Real &tol)
virtual Real norm() const =0
Returns where .
const Ptr< CombinedStatusTest< Real > > status_
Real testComplementarity(const Vector< Real > &x)
void initialize(const Vector< Real > &x, const Vector< Real > &g, const Vector< Real > &mul, const Vector< Real > &c)
Defines the general constraint operator interface.