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 Real stol = oem6*std::min(gtol,ctol);
74 list_.sublist(
"Status Test").set(
"Gradient Tolerance", gtol);
75 list_.sublist(
"Status Test").set(
"Constraint Tolerance", ctol);
76 list_.sublist(
"Status Test").set(
"Step Tolerance", stol);
77 list_.sublist(
"Status Test").set(
"Iteration Limit", maxit);
79 stepname_ = steplist.sublist(
"Subproblem").get(
"Step Type",
"Augmented Lagrangian");
82 verbosity_ = list.sublist(
"General").get(
"Output Level", 0);
88 template<
typename Real>
98 std::ostream &outStream) {
100 if (proj_ == nullPtr) {
101 proj_ = makePtr<PolyhedralProjection<Real>>(makePtrFromRef(bnd));
102 hasPolyProj_ =
false;
104 proj_->project(x,outStream);
111 updateState(x,l,myobj,bnd,con,pwa,dwa,outStream);
115 template<
typename Real>
123 std::ostream &outStream) {
125 Real zerotol = std::sqrt(ROL_EPSILON<Real>());
127 if (state_->iter == 0) {
140 state_->gradientVec->plus(dwa);
143 pwa.
axpy(-one,state_->gradientVec->dual());
144 proj_->project(pwa,outStream);
148 con.
value(*state_->constraintVec, x, zerotol);
149 state_->cnorm = state_->constraintVec->norm();
151 state_->gnorm = std::max(gnorm_,compViolation_);
158 template<
typename Real>
166 std::ostream &outStream ) {
168 Ptr<Vector<Real>> pwa = x.
clone(), dwa = g.
clone();
171 x,g,state_->searchSize,updateMultiplier_,
173 initialize(x,g,emul,eres,myobj,bnd,econ,*pwa,*dwa,outStream);
174 Ptr<TypeE::Algorithm<Real>> algo;
177 if (verbosity_ > 0) writeOutput(outStream,
true);
179 while (status_->check(*state_)) {
181 algo = TypeE::AlgorithmFactory<Real>(list_);
183 if (hasPolyProj_) algo->run(x,g,myobj,econ,emul,eres,
184 *proj_->getLinearConstraint(),
185 *proj_->getMultiplier(),
186 *proj_->getResidual(),outStream);
187 else algo->run(x,g,myobj,econ,emul,eres,outStream);
188 subproblemIter_ = algo->getState()->iter;
189 state_->nfval += algo->getState()->nfval;
190 state_->ngrad += algo->getState()->ngrad;
191 state_->ncval += algo->getState()->ncval;
194 state_->stepVec->set(x);
195 state_->stepVec->axpy(-one,*state_->iterateVec);
196 state_->snorm = state_->stepVec->norm();
197 state_->lagmultVec->axpy(-one,emul);
198 state_->snorm += state_->lagmultVec->norm();
201 state_->iterateVec->set(x);
202 state_->lagmultVec->set(emul);
208 updateState(x,emul,myobj,bnd,econ,*pwa,*dwa);
211 if (updatePenalty_) {
212 state_->searchSize *= tau_;
213 state_->searchSize = std::min(state_->searchSize,maxPenalty_);
218 if (verbosity_ > 0) writeOutput(outStream,printHeader_);
223 template<
typename Real>
225 std::stringstream hist;
226 if (verbosity_ > 1) {
227 hist << std::string(109,
'-') << std::endl;
228 hist <<
"Moreau-Yosida Penalty Solver";
229 hist <<
" status output definitions" << std::endl << std::endl;
230 hist <<
" iter - Number of iterates (steps taken)" << std::endl;
231 hist <<
" fval - Objective function value" << std::endl;
232 hist <<
" cnorm - Norm of the constraint" << std::endl;
233 hist <<
" gLnorm - Norm of the gradient of the Lagrangian" << std::endl;
234 hist <<
" ifeas - Infeasibility metric" << std::endl;
235 hist <<
" snorm - Norm of the step (update to optimization vector)" << std::endl;
236 hist <<
" penalty - Penalty parameter for bound constraints" << std::endl;
237 hist <<
" #fval - Cumulative number of times the objective function was evaluated" << std::endl;
238 hist <<
" #grad - Cumulative number of times the gradient was computed" << std::endl;
239 hist <<
" #cval - Cumulative number of times the constraint was evaluated" << std::endl;
240 hist <<
" subiter - Number of subproblem iterations" << std::endl;
241 hist << std::string(109,
'-') << std::endl;
245 hist << std::setw(6) << std::left <<
"iter";
246 hist << std::setw(15) << std::left <<
"fval";
247 hist << std::setw(15) << std::left <<
"cnorm";
248 hist << std::setw(15) << std::left <<
"gLnorm";
249 hist << std::setw(15) << std::left <<
"ifeas";
250 hist << std::setw(15) << std::left <<
"snorm";
251 hist << std::setw(10) << std::left <<
"penalty";
252 hist << std::setw(8) << std::left <<
"#fval";
253 hist << std::setw(8) << std::left <<
"#grad";
254 hist << std::setw(8) << std::left <<
"#cval";
255 hist << std::setw(8) << std::left <<
"subIter";
260 template<
typename Real>
262 std::stringstream hist;
263 hist << std::endl <<
"Moreau-Yosida Penalty Solver (Type G, General Constraints)";
265 hist <<
"Subproblem Solver: " << stepname_ << std::endl;
269 template<
typename Real>
271 std::stringstream hist;
272 hist << std::scientific << std::setprecision(6);
273 if ( state_->iter == 0 ) writeName(os);
274 if ( print_header ) writeHeader(os);
275 if ( state_->iter == 0 ) {
277 hist << std::setw(6) << std::left << state_->iter;
278 hist << std::setw(15) << std::left << state_->value;
279 hist << std::setw(15) << std::left << state_->cnorm;
280 hist << std::setw(15) << std::left << gnorm_;
281 hist << std::setw(15) << std::left << compViolation_;
282 hist << std::setw(15) << std::left <<
"---";
283 hist << std::scientific << std::setprecision(2);
284 hist << std::setw(10) << std::left << state_->searchSize;
285 hist << std::setw(8) << std::left << state_->nfval;
286 hist << std::setw(8) << std::left << state_->ngrad;
287 hist << std::setw(8) << std::left << state_->ncval;
288 hist << std::setw(8) << std::left <<
"---";
293 hist << std::setw(6) << std::left << state_->iter;
294 hist << std::setw(15) << std::left << state_->value;
295 hist << std::setw(15) << std::left << state_->cnorm;
296 hist << std::setw(15) << std::left << gnorm_;
297 hist << std::setw(15) << std::left << compViolation_;
298 hist << std::setw(15) << std::left << state_->snorm;
299 hist << std::scientific << std::setprecision(2);
300 hist << std::setw(10) << std::left << state_->searchSize;
301 hist << std::scientific << std::setprecision(6);
302 hist << std::setw(8) << std::left << state_->nfval;
303 hist << std::setw(8) << std::left << state_->ngrad;
304 hist << std::setw(8) << std::left << state_->ncval;
305 hist << 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.
MoreauYosidaAlgorithm(ParameterList &list)
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.
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.
virtual void writeExitStatus(std::ostream &os) const
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.
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 .
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.