ROL
ROL_AugmentedLagrangian_SimOpt.hpp
Go to the documentation of this file.
1// @HEADER
2// ************************************************************************
3//
4// Rapid Optimization Library (ROL) Package
5// Copyright (2014) Sandia Corporation
6//
7// Under terms of Contract DE-AC04-94AL85000, there is a non-exclusive
8// license for use of this work by or on behalf of the U.S. Government.
9//
10// Redistribution and use in source and binary forms, with or without
11// modification, are permitted provided that the following conditions are
12// met:
13//
14// 1. Redistributions of source code must retain the above copyright
15// notice, this list of conditions and the following disclaimer.
16//
17// 2. Redistributions in binary form must reproduce the above copyright
18// notice, this list of conditions and the following disclaimer in the
19// documentation and/or other materials provided with the distribution.
20//
21// 3. Neither the name of the Corporation nor the names of the
22// contributors may be used to endorse or promote products derived from
23// this software without specific prior written permission.
24//
25// THIS SOFTWARE IS PROVIDED BY SANDIA CORPORATION "AS IS" AND ANY
26// EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
27// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
28// PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL SANDIA CORPORATION OR THE
29// CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
30// EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
31// PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
32// PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
33// LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
34// NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
35// SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
36//
37// Questions? Contact lead developers:
38// Drew Kouri (dpkouri@sandia.gov) and
39// Denis Ridzal (dridzal@sandia.gov)
40//
41// ************************************************************************
42// @HEADER
43
44#ifndef ROL_AUGMENTEDLAGRANGIAN_SIMOPT_H
45#define ROL_AUGMENTEDLAGRANGIAN_SIMOPT_H
46
50#include "ROL_Vector.hpp"
51#include "ROL_Types.hpp"
52#include "ROL_Ptr.hpp"
53#include <iostream>
54
94namespace ROL {
95
96template <class Real>
98private:
99 // Required for Augmented Lagrangian definition
100 const ROL::Ptr<Objective_SimOpt<Real> > obj_;
101 ROL::Ptr<QuadraticPenalty_SimOpt<Real> > pen_;
103
104 // Auxiliary storage
105 ROL::Ptr<Vector<Real> > dualSimVector_;
106 ROL::Ptr<Vector<Real> > dualOptVector_;
107
108 // Objective and constraint evaluations
109 Real fval_;
110 ROL::Ptr<Vector<Real> > gradient1_;
111 ROL::Ptr<Vector<Real> > gradient2_;
112
113 // Evaluation counters
116
117 // User defined options
119
120 // Flags to recompute quantities
124
125public:
127 const ROL::Ptr<Constraint_SimOpt<Real> > &con,
128 const Vector<Real> &multiplier,
129 const Real penaltyParameter,
130 const Vector<Real> &simVec,
131 const Vector<Real> &optVec,
132 const Vector<Real> &conVec,
133 ROL::ParameterList &parlist)
134 : obj_(obj), penaltyParameter_(penaltyParameter),
135 fval_(0), nfval_(0), ngval_(0), isValueComputed_(false),
137
138 gradient1_ = simVec.dual().clone();
139 gradient2_ = optVec.dual().clone();
140 dualSimVector_ = simVec.dual().clone();
141 dualOptVector_ = optVec.dual().clone();
142
143 ROL::ParameterList& sublist = parlist.sublist("Step").sublist("Augmented Lagrangian");
144 scaleLagrangian_ = sublist.get("Use Scaled Augmented Lagrangian", false);
145 int HessianApprox = sublist.get("Level of Hessian Approximation", 0);
146
147 pen_ = ROL::makePtr<QuadraticPenalty_SimOpt<Real>>(con,multiplier,penaltyParameter,simVec,optVec,conVec,scaleLagrangian_,HessianApprox);
148 }
149
150 virtual void update( const Vector<Real> &u, const Vector<Real> &z, bool flag = true, int iter = -1 ) {
151 obj_->update(u,z,flag,iter);
152 pen_->update(u,z,flag,iter);
153 isValueComputed_ = (flag ? false : isValueComputed_);
156 }
157
158 virtual Real value( const Vector<Real> &u, const Vector<Real> &z, Real &tol ) {
159 // Compute objective function value
160 if ( !isValueComputed_ ) {
161 fval_ = obj_->value(u,z,tol); nfval_++;
162 isValueComputed_ = true;
163 }
164 // Compute penalty term
165 Real pval = pen_->value(u,z,tol);
166 // Compute augmented Lagrangian
167 Real val = fval_;
168 if (scaleLagrangian_) {
169 val /= penaltyParameter_;
170 }
171 return val + pval;
172 }
173
174 virtual void gradient_1( Vector<Real> &g, const Vector<Real> &u, const Vector<Real> &z, Real &tol ) {
175 // Compute objective function gradient
176 if ( !isGradient1Computed_ ) {
177 obj_->gradient_1(*gradient1_,u,z,tol); ngval_++;
179 }
180 g.set(*gradient1_);
181 // Compute gradient of penalty
182 pen_->gradient_1(*dualSimVector_,u,z,tol);
183 // Compute gradient of Augmented Lagrangian
184 if ( scaleLagrangian_ ) {
185 g.scale(static_cast<Real>(1)/penaltyParameter_);
186 }
188 }
189
190 virtual void gradient_2( Vector<Real> &g, const Vector<Real> &u, const Vector<Real> &z, Real &tol ) {
191 // Compute objective function gradient
192 if ( !isGradient2Computed_ ) {
193 obj_->gradient_2(*gradient2_,u,z,tol); ngval_++;
195 }
196 g.set(*gradient2_);
197 // Compute gradient of penalty
198 pen_->gradient_2(*dualOptVector_,u,z,tol);
199 // Compute gradient of Augmented Lagrangian
200 if ( scaleLagrangian_ ) {
201 g.scale(static_cast<Real>(1)/penaltyParameter_);
202 }
204 }
205
206 virtual void hessVec_11( Vector<Real> &hv, const Vector<Real> &v,
207 const Vector<Real> &u, const Vector<Real> &z, Real &tol ) {
208 // Apply objective Hessian to a vector
209 obj_->hessVec_11(hv,v,u,z,tol);
210 // Apply penalty Hessian to a vector
211 pen_->hessVec_11(*dualSimVector_,v,u,z,tol);
212 // Build hessVec of Augmented Lagrangian
213 if ( scaleLagrangian_ ) {
214 hv.scale(static_cast<Real>(1)/penaltyParameter_);
215 }
216 hv.plus(*dualSimVector_);
217 }
218
219 virtual void hessVec_12( Vector<Real> &hv, const Vector<Real> &v,
220 const Vector<Real> &u, const Vector<Real> &z, Real &tol ) {
221 // Apply objective Hessian to a vector
222 obj_->hessVec_12(hv,v,u,z,tol);
223 // Apply penalty Hessian to a vector
224 pen_->hessVec_12(*dualSimVector_,v,u,z,tol);
225 // Build hessVec of Augmented Lagrangian
226 if ( scaleLagrangian_ ) {
227 hv.scale(static_cast<Real>(1)/penaltyParameter_);
228 }
229 hv.plus(*dualSimVector_);
230 }
231
232 virtual void hessVec_21( Vector<Real> &hv, const Vector<Real> &v,
233 const Vector<Real> &u, const Vector<Real> &z, Real &tol ) {
234 // Apply objective Hessian to a vector
235 obj_->hessVec_21(hv,v,u,z,tol);
236 // Apply penalty Hessian to a vector
237 pen_->hessVec_21(*dualOptVector_,v,u,z,tol);
238 // Build hessVec of Augmented Lagrangian
239 if ( scaleLagrangian_ ) {
240 hv.scale(static_cast<Real>(1)/penaltyParameter_);
241 }
242 hv.plus(*dualOptVector_);
243 }
244
245 virtual void hessVec_22( Vector<Real> &hv, const Vector<Real> &v,
246 const Vector<Real> &u, const Vector<Real> &z, Real &tol ) {
247 // Apply objective Hessian to a vector
248 obj_->hessVec_22(hv,v,u,z,tol);
249 // Apply penalty Hessian to a vector
250 pen_->hessVec_22(*dualOptVector_,v,u,z,tol);
251 // Build hessVec of Augmented Lagrangian
252 if ( scaleLagrangian_ ) {
253 hv.scale(static_cast<Real>(1)/penaltyParameter_);
254 }
255 hv.plus(*dualOptVector_);
256 }
257
258 // Return objective function value
259 virtual Real getObjectiveValue(const Vector<Real> &u, const Vector<Real> &z) {
260 Real tol = std::sqrt(ROL_EPSILON<Real>());
261 // Evaluate objective function value
262 if ( !isValueComputed_ ) {
263 fval_ = obj_->value(u,z,tol); nfval_++;
264 isValueComputed_ = true;
265 }
266 return fval_;
267 }
268
269 // Return constraint value
270 virtual void getConstraintVec(Vector<Real> &c, const Vector<Real> &u, const Vector<Real> &z) {
271 pen_->getConstraintVec(c,u,z);
272 }
273
274 // Return total number of constraint evaluations
275 virtual int getNumberConstraintEvaluations(void) const {
276 return pen_->getNumberConstraintEvaluations();
277 }
278
279 // Return total number of objective evaluations
280 virtual int getNumberFunctionEvaluations(void) const {
281 return nfval_;
282 }
283
284 // Return total number of gradient evaluations
285 virtual int getNumberGradientEvaluations(void) const {
286 return ngval_;
287 }
288
289 // Reset with upated penalty parameter
290 virtual void reset(const Vector<Real> &multiplier, const Real penaltyParameter) {
291 nfval_ = 0; ngval_ = 0;
292 pen_->reset(multiplier,penaltyParameter);
293 }
294}; // class AugmentedLagrangian
295
296} // namespace ROL
297
298#endif
Contains definitions of custom data types in ROL.
Provides the interface to evaluate the SimOpt augmented Lagrangian.
virtual Real getObjectiveValue(const Vector< Real > &u, const Vector< Real > &z)
AugmentedLagrangian_SimOpt(const ROL::Ptr< Objective_SimOpt< Real > > &obj, const ROL::Ptr< Constraint_SimOpt< Real > > &con, const Vector< Real > &multiplier, const Real penaltyParameter, const Vector< Real > &simVec, const Vector< Real > &optVec, const Vector< Real > &conVec, ROL::ParameterList &parlist)
virtual Real value(const Vector< Real > &u, const Vector< Real > &z, Real &tol)
Compute value.
virtual void getConstraintVec(Vector< Real > &c, const Vector< Real > &u, const Vector< Real > &z)
virtual void hessVec_22(Vector< Real > &hv, const Vector< Real > &v, const Vector< Real > &u, const Vector< Real > &z, Real &tol)
virtual void update(const Vector< Real > &u, const Vector< Real > &z, bool flag=true, int iter=-1)
Update objective function. u is an iterate, z is an iterate, flag = true if the iterate has changed...
virtual void gradient_2(Vector< Real > &g, const Vector< Real > &u, const Vector< Real > &z, Real &tol)
Compute gradient with respect to second component.
virtual void reset(const Vector< Real > &multiplier, const Real penaltyParameter)
virtual void hessVec_12(Vector< Real > &hv, const Vector< Real > &v, const Vector< Real > &u, const Vector< Real > &z, Real &tol)
virtual void hessVec_11(Vector< Real > &hv, const Vector< Real > &v, const Vector< Real > &u, const Vector< Real > &z, Real &tol)
Apply Hessian approximation to vector.
virtual void hessVec_21(Vector< Real > &hv, const Vector< Real > &v, const Vector< Real > &u, const Vector< Real > &z, Real &tol)
const ROL::Ptr< Objective_SimOpt< Real > > obj_
ROL::Ptr< QuadraticPenalty_SimOpt< Real > > pen_
virtual void gradient_1(Vector< Real > &g, const Vector< Real > &u, const Vector< Real > &z, Real &tol)
Compute gradient with respect to first component.
Defines the constraint operator interface for simulation-based optimization.
Provides the interface to evaluate simulation-based objective functions.
Defines the linear algebra or vector space interface.
virtual void set(const Vector &x)
Set where .
virtual void scale(const Real alpha)=0
Compute where .
virtual const Vector & dual() const
Return dual representation of , for example, the result of applying a Riesz map, or change of basis,...
virtual void plus(const Vector &x)=0
Compute , where .
virtual ROL::Ptr< Vector > clone() const =0
Clone to make a new (uninitialized) vector.