ROL
ROL_CauchyPoint.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_CAUCHYPOINT_H
45#define ROL_CAUCHYPOINT_H
46
51#include "ROL_TrustRegion.hpp"
52#include "ROL_Vector.hpp"
53#include "ROL_Types.hpp"
54#include "ROL_ParameterList.hpp"
55
56namespace ROL {
57
58template<class Real>
59class CauchyPoint : public TrustRegion<Real> {
60private:
61
62 ROL::Ptr<Vector<Real> > g_;
63 ROL::Ptr<Vector<Real> > p_;
64 ROL::Ptr<Vector<Real> > Hp_;
65
66 Real pRed_;
67 Real eps_;
68 Real alpha_;
69
71
72public:
73
74 // Constructor
75 CauchyPoint( ROL::ParameterList &parlist )
76 : TrustRegion<Real>(parlist), pRed_(0), alpha_(-1), useCGTCP_(false) {
77 // Unravel Parameter List
78 Real oe2(100);
79 Real TRsafe = parlist.sublist("Step").sublist("Trust Region").get("Safeguard Size",oe2);
80 eps_ = TRsafe*ROL_EPSILON<Real>();
81 }
82
83 void initialize( const Vector<Real> &x, const Vector<Real> &s, const Vector<Real> &g) {
85 Hp_ = g.clone();
86 p_ = s.clone();
87// if ( useCGTCP_ ) {
88// g_ = g.clone();
89// p_ = s.clone();
90// }
91 }
92
93 void run( Vector<Real> &s,
94 Real &snorm,
95 int &iflag,
96 int &iter,
97 const Real del,
99 //if ( pObj.isConActivated() ) {
100 // if ( useCGTCP_ ) {
101 // cauchypoint_CGT( s, snorm, iflag, iter, del, model );
102 // }
103 // else {
104 // cauchypoint_M( s, snorm, iflag, iter, del, model );
105 // }
106 //}
107 //else {
108 // cauchypoint_unc( s, snorm, iflag, iter, del, model );
109 //}
110 cauchypoint_unc( s, snorm, iflag, iter, del, model );
112 }
113
114private:
116 Real &snorm,
117 int &iflag,
118 int &iter,
119 const Real del,
120 TrustRegionModel<Real> &model) {
121 Real tol = std::sqrt(ROL_EPSILON<Real>());
122 // Set step to (projected) gradient
123 model.dualTransform(*Hp_,*model.getGradient());
124 s.set(Hp_->dual());
125 // Apply (reduced) Hessian to (projected) gradient
126 model.hessVec(*Hp_,s,s,tol);
127 Real gBg = Hp_->dot(s.dual());
128 Real gnorm = s.dual().norm();
129 Real gg = gnorm*gnorm;
130 Real alpha = del/gnorm;
131 if ( gBg > ROL_EPSILON<Real>() ) {
132 alpha = std::min(gg/gBg, del/gnorm);
133 }
134
135 s.scale(-alpha);
136 model.primalTransform(*p_,s);
137 s.set(*p_);
138 snorm = s.norm(); //alpha*gnorm;
139 iflag = 0;
140 iter = 0;
141 pRed_ = alpha*(gg - static_cast<Real>(0.5)*alpha*gBg);
142 }
143
144// void cauchypoint_M( Vector<Real> &s,
145// Real &snorm,
146// int &iflag,
147// int &iter,
148// const Real del,
149// const Vector<Real> &x,
150// TrustRegionModel<Real> &model,
151// BoundConstraint<Real> &bnd) {
152// Real tol = std::sqrt(ROL_EPSILON<Real>()),
153// const Real zero(0), half(0.5), oe4(1.e4), two(2);
154// // Parameters
155// Real mu0(1.e-2), mu1(1), beta1(0), beta2(0);
156// bool decr = true;
157// bool stat = true;
158// // Initial step length
159// Real alpha = (alpha_ > zero ? alpha_ : one);
160// Real alpha0 = alpha;
161// Real alphamax = oe4*alpha;
162// // Set step to (projected) gradient
163// s.zero();
164// model.gradient(*Hp_,s,tol);
165// s.set(Hp_->dual());
166// // Initial model value
167// s.scale(-alpha);
168// bnd.computeProjectedStep(s,x);
169// snorm = s.norm();
170// Real val = model.value(s,tol);
171// Real val0 = val;
172//
173// // Determine whether to increase or decrease alpha
174// if ( val > mu0 * gs || snorm > mu1 * del ) {
175// beta1 = half;
176// beta2 = half;
177// decr = true;
178// }
179// else {
180// beta1 = two;
181// beta2 = two;
182// decr = false;
183// }
184//
185// while ( stat ) {
186// // Update step length
187// alpha0 = alpha;
188// val0 = val;
189// alpha *= half*(beta1+beta2);
190//
191// // Update model value
192// s.set(grad.dual());
193// s.scale(-alpha);
194// pObj.computeProjectedStep(s,x);
195// snorm = s.norm();
196// pObj.hessVec(*Hp_,s,x,tol);
197// gs = s.dot(grad.dual());
198// val = gs + half*s.dot(Hp_->dual());
199//
200// // Update termination criterion
201// if ( decr ) {
202// stat = ( val > mu0 * gs || snorm > mu1 * del );
203// if ( std::abs(val) < eps_ && std::abs(mu0 *gs) < eps_ ) {
204// stat = (snorm > mu1 * del);
205// }
206// }
207// else {
208// stat = !( val > mu0 * gs || snorm > mu1 * del );
209// if ( std::abs(val) < eps_ && std::abs(mu0 *gs) < eps_ ) {
210// stat = !(snorm > mu1 * del);
211// }
212// if ( alpha > alphamax ) {
213// stat = false;
214// }
215// }
216// }
217// // Reset to last 'successful' step
218// val = val0;
219// alpha = alpha0;
220// s.set(grad.dual());
221// s.scale(-alpha);
222// pObj.computeProjectedStep(s,x);
223// snorm = s.norm();
224//
225// alpha_ = alpha;
226// pRed_ = -val;
227// }
228//
229// void cauchypoint_CGT( Vector<Real> &s, Real &snorm, Real &del, int &iflag, int &iter, const Vector<Real> &x,
230// const Vector<Real> &grad, const Real &gnorm, ProjectedObjective<Real> &pObj ) {
231// Real tol = std::sqrt(ROL_EPSILON<Real>()), one(1), half(0.5), two(2);
232// bool tmax_flag = true;
233// int maxit = 20;
234// Real t = del/gnorm;
235// Real tmax(1.e10), tmin(0), gs(0), pgnorm(0);
236// Real c1(0.25), c2(0.75), c3(0.9), c4(0.25);
237// for ( int i = 0; i < maxit; i++ ) {
238// // Compute p = x + s = P(x - t*g)
239// p_->set(x);
240// p_->axpy(-t,grad.dual());
241// pObj.project(*p_);
242// // Compute s = p - x = P(x - t*g) - x
243// s.set(*p_);
244// s.axpy(-one,x);
245// snorm = s.norm();
246// // Evaluate Model
247// pObj.hessVec(*Hp_,s,x,tol);
248// gs = s.dot(grad.dual());
249// pRed_ = -gs - half*s.dot(Hp_->dual());
250//
251// // Check Stopping Conditions
252// g_->set(grad);
253// pObj.pruneActive(*g_,grad,*p_); // Project gradient onto tangent cone at p
254// pgnorm = g_->norm();
255// if ( snorm > del || pRed_ < -c2*gs ) {
256// tmax = t;
257// tmax_flag = false;
258// }
259// else if ( snorm < c3*del && pRed_ > -c1*gs && pgnorm > c4*std::abs(gs)/del ) {
260// tmin = t;
261// }
262// else {
263// break;
264// }
265//
266// // Update t
267// if ( tmax_flag ) {
268// t *= two;
269// }
270// else {
271// t = half*(tmax + tmin);
272// }
273// }
274// }
275};
276
277}
278
279#endif
Contains definitions of custom data types in ROL.
Provides interface for the Cauchy point trust-region subproblem solver.
void run(Vector< Real > &s, Real &snorm, int &iflag, int &iter, const Real del, TrustRegionModel< Real > &model)
void cauchypoint_unc(Vector< Real > &s, Real &snorm, int &iflag, int &iter, const Real del, TrustRegionModel< Real > &model)
ROL::Ptr< Vector< Real > > g_
ROL::Ptr< Vector< Real > > Hp_
void initialize(const Vector< Real > &x, const Vector< Real > &s, const Vector< Real > &g)
ROL::Ptr< Vector< Real > > p_
CauchyPoint(ROL::ParameterList &parlist)
Provides the interface to evaluate trust-region model functions.
virtual void dualTransform(Vector< Real > &tv, const Vector< Real > &v)
virtual const Ptr< const Vector< Real > > getGradient(void) const
virtual void primalTransform(Vector< Real > &tv, const Vector< Real > &v)
virtual void hessVec(Vector< Real > &hv, const Vector< Real > &v, const Vector< Real > &s, Real &tol)
Apply Hessian approximation to vector.
Provides interface for and implements trust-region subproblem solvers.
virtual void initialize(const Vector< Real > &x, const Vector< Real > &s, const Vector< Real > &g)
void setPredictedReduction(const Real pRed)
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 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,...
Definition: ROL_Vector.hpp:226
virtual ROL::Ptr< Vector > clone() const =0
Clone to make a new (uninitialized) vector.