ROL
ROL_TypeB_MoreauYosidaAlgorithm_Def.hpp
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43
44#ifndef ROL_TYPEB_MOREAUYOSIDAALGORITHM_DEF_HPP
45#define ROL_TYPEB_MOREAUYOSIDAALGORITHM_DEF_HPP
46
48
49namespace ROL {
50namespace TypeB {
51
52template<typename Real>
54 : TypeB::Algorithm<Real>::Algorithm(),
55 tau_(10), print_(false), list_(list), subproblemIter_(0) {
56 // Set status test
57 status_->reset();
58 status_->add(makePtr<StatusTest<Real>>(list));
59
60 // Parse parameters
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);
66 updatePenalty_ = steplist.get("Update Penalty", true);
67 updateMultiplier_ = steplist.get("Update Multiplier", true);
68 print_ = steplist.sublist("Subproblem").get("Print History", false);
69 // Set parameters for step subproblem
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);
78 // Get step name from parameterlist
79 stepname_ = steplist.sublist("Subproblem").get("Step Type","Trust Region");
80
81 // Output settings
82 verbosity_ = list.sublist("General").get("Output Level", 0);
84 print_ = (verbosity_ > 2 ? true : print_);
85 list_.sublist("General").set("Output Level",(print_ ? verbosity_ : 0));
86}
87
88template<typename Real>
90 const Vector<Real> &g,
93 Vector<Real> &pwa,
94 std::ostream &outStream) {
95 hasEcon_ = true;
96 if (proj_ == nullPtr) {
97 proj_ = makePtr<PolyhedralProjection<Real>>(makePtrFromRef(bnd));
98 hasEcon_ = false;
99 }
100 // Initialize data
102 // Initialize the algorithm state
103 state_->nfval = 0;
104 state_->ngrad = 0;
105 updateState(x,myobj,bnd,pwa,outStream);
106}
107
108
109template<typename Real>
113 Vector<Real> &pwa,
114 std::ostream &outStream) {
115 const Real one(1);
116 Real zerotol = std::sqrt(ROL_EPSILON<Real>());
117 // Update objective and constraint.
118 if (state_->iter == 0) {
119 myobj.update(x,UpdateType::Initial,state_->iter);
120 }
121 //else {
122 // myobj.update(x,UpdateType::Accept,state_->iter);
123 //}
124 // Compute norm of the gradient of the Lagrangian
125 state_->value = myobj.getObjectiveValue(x, zerotol);
126 myobj.getObjectiveGradient(*state_->gradientVec, x, zerotol);
127 //myobj.gradient(*state_->gradientVec, x, zerotol);
128 //gnorm_ = state_->gradientVec->norm();
129 pwa.set(x);
130 pwa.axpy(-one,state_->gradientVec->dual());
131 proj_->project(pwa,outStream);
132 pwa.axpy(-one,x);
133 gnorm_ = pwa.norm();
134 // Compute constraint violation
135 compViolation_ = myobj.testComplementarity(x);
136 state_->gnorm = std::max(gnorm_,compViolation_);
137 // Update state
138 state_->nfval++;
139 state_->ngrad++;
140}
141
142template<typename Real>
144 const Vector<Real> &g,
145 Objective<Real> &obj,
147 std::ostream &outStream ) {
148 const Real one(1);
149 Ptr<Vector<Real>> pwa = x.clone();
150 // Initialize Moreau-Yosida data
151 MoreauYosidaObjective<Real> myobj(makePtrFromRef(obj),makePtrFromRef(bnd),
152 x,g,state_->searchSize,updateMultiplier_,
153 updatePenalty_);
154 initialize(x,g,myobj,bnd,*pwa,outStream);
155 Ptr<TypeU::Algorithm<Real>> algo;
156
157 // Output
158 if (verbosity_ > 0) writeOutput(outStream,true);
159
160 while (status_->check(*state_)) {
161 // Solve augmented Lagrangian subproblem
162 algo = TypeU::AlgorithmFactory<Real>(list_);
163 if (hasEcon_) algo->run(x,g,myobj,*proj_->getLinearConstraint(),
164 *proj_->getMultiplier(),*proj_->getResidual(),
165 outStream);
166 else algo->run(x,g,myobj,outStream);
167 subproblemIter_ = algo->getState()->iter;
168
169 // Compute step
170 state_->stepVec->set(x);
171 state_->stepVec->axpy(-one,*state_->iterateVec);
172 state_->snorm = state_->stepVec->norm();
173
174 // Update iterate and Lagrange multiplier
175 state_->iterateVec->set(x);
176
177 // Update objective and constraint
178 state_->iter++;
179
180 // Update state
181 updateState(x,myobj,bnd,*pwa,outStream);
182
183 // Update multipliers
184 if (updatePenalty_) {
185 state_->searchSize *= tau_;
186 state_->searchSize = std::min(state_->searchSize,maxPenalty_);
187 }
188 myobj.updateMultipliers(state_->searchSize,x);
189
190 state_->nfval += myobj.getNumberFunctionEvaluations() + algo->getState()->nfval;
191 state_->ngrad += myobj.getNumberGradientEvaluations() + algo->getState()->ngrad;
192
193 // Update Output
194 if (verbosity_ > 0) writeOutput(outStream,writeHeader_);
195 }
196 if (verbosity_ > 0) TypeB::Algorithm<Real>::writeExitStatus(outStream);
197}
198
199template<typename Real>
200void MoreauYosidaAlgorithm<Real>::writeHeader( std::ostream& os ) const {
201 std::stringstream hist;
202 if (verbosity_ > 1) {
203 hist << std::string(109,'-') << std::endl;
204 hist << "Moreau-Yosida Penalty Solver";
205 hist << " status output definitions" << std::endl << std::endl;
206 hist << " iter - Number of iterates (steps taken)" << std::endl;
207 hist << " fval - Objective function value" << std::endl;
208 hist << " gnorm - Norm of the gradient" << std::endl;
209 hist << " ifeas - Infeasibility metric" << std::endl;
210 hist << " snorm - Norm of the step (update to optimization vector)" << std::endl;
211 hist << " penalty - Penalty parameter for bound constraints" << std::endl;
212 hist << " #fval - Cumulative number of times the objective function was evaluated" << std::endl;
213 hist << " #grad - Cumulative number of times the gradient was computed" << std::endl;
214 hist << " subiter - Number of subproblem iterations" << std::endl;
215 hist << std::string(109,'-') << std::endl;
216 }
217
218 hist << " ";
219 hist << std::setw(6) << std::left << "iter";
220 hist << std::setw(15) << std::left << "fval";
221 hist << std::setw(15) << std::left << "gnorm";
222 hist << std::setw(15) << std::left << "ifeas";
223 hist << std::setw(15) << std::left << "snorm";
224 hist << std::setw(10) << std::left << "penalty";
225 hist << std::setw(8) << std::left << "#fval";
226 hist << std::setw(8) << std::left << "#grad";
227 hist << std::setw(8) << std::left << "subIter";
228 hist << std::endl;
229 os << hist.str();
230}
231
232template<typename Real>
233void MoreauYosidaAlgorithm<Real>::writeName( std::ostream& os ) const {
234 std::stringstream hist;
235 hist << std::endl << " Moreau-Yosida Penalty Solver";
236 hist << std::endl;
237 os << hist.str();
238}
239
240template<typename Real>
241void MoreauYosidaAlgorithm<Real>::writeOutput( std::ostream& os, bool write_header ) const {
242 std::stringstream hist;
243 hist << std::scientific << std::setprecision(6);
244 if ( state_->iter == 0 ) writeName(os);
245 if ( write_header ) writeHeader(os);
246 if ( state_->iter == 0 ) {
247 hist << " ";
248 hist << std::setw(6) << std::left << state_->iter;
249 hist << std::setw(15) << std::left << state_->value;
250 hist << std::setw(15) << std::left << gnorm_;
251 hist << std::setw(15) << std::left << compViolation_;
252 hist << std::setw(15) << std::left << "---";
253 hist << std::scientific << std::setprecision(2);
254 hist << std::setw(10) << std::left << state_->searchSize;
255 hist << std::scientific << std::setprecision(6);
256 hist << std::setw(8) << std::left << state_->nfval;
257 hist << std::setw(8) << std::left << state_->ngrad;
258 hist << std::setw(8) << std::left << "---";
259 hist << std::endl;
260 }
261 else {
262 hist << " ";
263 hist << std::setw(6) << std::left << state_->iter;
264 hist << std::setw(15) << std::left << state_->value;
265 hist << std::setw(15) << std::left << gnorm_;
266 hist << std::setw(15) << std::left << compViolation_;
267 hist << std::setw(15) << std::left << state_->snorm;
268 hist << std::scientific << std::setprecision(2);
269 hist << std::setw(10) << std::left << state_->searchSize;
270 hist << std::scientific << std::setprecision(6);
271 hist << std::setw(8) << std::left << state_->nfval;
272 hist << std::setw(8) << std::left << state_->ngrad;
273 hist << std::setw(8) << std::left << subproblemIter_;
274 hist << std::endl;
275 }
276 os << hist.str();
277}
278
279} // namespace TypeB
280} // namespace ROL
281
282#endif
Provides the interface to apply upper and lower bound constraints.
Provides the interface to evaluate the Moreau-Yosida penalty function.
void getObjectiveGradient(Vector< Real > &g, const Vector< Real > &x, Real &tol)
Real getObjectiveValue(const Vector< Real > &x, Real &tol)
Real testComplementarity(const Vector< Real > &x)
void update(const Vector< Real > &x, UpdateType type, int iter=-1)
Update Moreau-Yosida penalty function.
void updateMultipliers(Real mu, const Vector< Real > &x)
Provides the interface to evaluate objective functions.
Provides an interface to check status of optimization algorithms.
Provides an interface to run bound constrained optimization algorithms.
void initialize(const Vector< Real > &x, const Vector< Real > &g)
virtual void writeExitStatus(std::ostream &os) const
const Ptr< AlgorithmState< Real > > state_
const Ptr< CombinedStatusTest< Real > > status_
void updateState(const Vector< Real > &x, MoreauYosidaObjective< Real > &myobj, BoundConstraint< Real > &bnd, Vector< Real > &pwa, std::ostream &outStream=std::cout)
void writeOutput(std::ostream &os, bool write_header=false) const override
Print iterate status.
void run(Vector< Real > &x, const Vector< Real > &g, Objective< Real > &obj, BoundConstraint< Real > &bnd, std::ostream &outStream=std::cout) override
Run algorithm on bound constrained problems (Type-B). This general interface supports the use of dual...
void writeName(std::ostream &os) const override
Print step name.
void initialize(Vector< Real > &x, const Vector< Real > &g, MoreauYosidaObjective< Real > &myobj, BoundConstraint< Real > &bnd, Vector< Real > &pwa, std::ostream &outStream=std::cout)
void writeHeader(std::ostream &os) const override
Print iterate header.
Defines the linear algebra or vector space interface.
Definition: ROL_Vector.hpp:84
virtual Real norm() const =0
Returns where .
virtual void set(const Vector &x)
Set where .
Definition: ROL_Vector.hpp:209
virtual ROL::Ptr< Vector > clone() const =0
Clone to make a new (uninitialized) vector.
virtual void axpy(const Real alpha, const Vector &x)
Compute where .
Definition: ROL_Vector.hpp:153