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// NOX: An Object-Oriented Nonlinear Solver Package
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#ifndef NOX_SOLVER_TRUSTREGIONBASED_H
#define NOX_SOLVER_TRUSTREGIONBASED_H
#include "NOX_Solver_Generic.H" // base class
#include "Teuchos_ParameterList.hpp" // class data element
#include "NOX_Utils.H" // class data element
#include "NOX_Solver_PrePostOperator.H" // class data element
// Forward declaration
namespace NOX {
class GlobalData;
namespace MeritFunction {
class Generic;
}
namespace Direction {
class Generic;
}
}
namespace NOX {
namespace Solver {
/*!
\brief %Newton-like solver using a trust region.
Our goal is to solve: \f$ F(x) = 0, \f$ where \f$ F:\Re^n \rightarrow
\Re^n \f$. Alternatively, we might say that we wish to solve
\f$
\min f(x) \equiv \frac{1}{2} \|F(x)\|^2_2.
\f$
The trust region subproblem (TRSP) at iteration \f$k\f$ is given by
\f$
\min \; m_k(s) \equiv f_k + g_k^T d + \frac{1}{2} d^T B_k d,
\mbox{ s.t. } \|d\| \leq \Delta_k
\quad \mbox{(TRSP)}
\f$
where
<ul>
<li>\f$ f_k = f(x_k) = \frac{1}{2} \|F(x_k)\|^2_2 \f$,
<li>\f$ g_k = \nabla f(x_k) = J(x_k)^T F(x_k) \f$,
<li>\f$ B_k = J(x_k)^T J(x_k) \approx \nabla^2 f(x_k) \f$,
<li>\f$ J(x_k)\f$ is the Jacobian of \f$F\f$ at \f$x_k\f$, and
<li>\f$ \Delta_k \f$ is the trust region radius.
</ul>
The "improvement ratio" for a given step \f$ s \f$ is defined as
\f$
\rho = \displaystyle\frac{ f(x_k) - f(x_k + d) } { m_k(0) - m_k(d) }
\f$
An iteration consists of the following steps.
<ul>
<li> Compute Newton-like direction: \f$n\f$
<li> Compute Cauchy-like direction: \f$c\f$
<li> If this is the first iteration, initialize \f$\Delta\f$ as
follows: If \f$\|n\|_2 < \Delta_{\min}\f$, then \f$\Delta = 2
\Delta_{\min}\f$; else, \f$\Delta = \|n\|_2\f$.
<li> Initialize \f$\rho = -1\f$
<li> While \f$\rho < \rho_{\min}\f$ and \f$\Delta > \Delta_{\min}\f$, do the following.
<ul>
<li> Compute the direction \f$d\f$ as follows:
<ul>
<li> If \f$\|n\|_2 < \Delta\f$, then take a Newton step by
setting \f$d = n\f$
<li> Otherwise if \f$\|c\|_2 > \Delta\f$, then take a Cauchy
step by setting \f$d =
\displaystyle\frac{\Delta}{\|c\|_2} c\f$
<li> Otherwise, take a Dog Leg step by setting
\f$ d = (1-\gamma) c + \gamma n \f$ where
\f$
\gamma = \displaystyle\frac
{-c^T a + \sqrt{ (c^Ta)^2 - (c^Tc - \Delta^2) a^Ta}}{a^Ta}
\f$
with \f$a = n-c\f$.
</ul>
<li> Set \f$x_{\rm new} = x + d\f$ and calculate \f$f_{\rm new}\f$
<li> If \f$f_{\rm new} \geq f\f$, then \f$\rho = -1\f$ Otherwise
\f$ \rho = \displaystyle \frac {f - f_{\rm new}} {| d^T J F
+ \frac{1}{2} (J d)^T (J d)|} \f$
</ul>
<li> Update the solution: \f$x = x_{\rm new}\f$
<li> Update trust region:
<ul>
<li> If \f$\rho < \rho_{\rm s}\f$ and \f$\|n\|_2 < \Delta\f$,
then shrink the trust region to the size of the Newton step:
\f$\Delta = \|n\|_2\f$.
<li> Otherwise if \f$\rho < \rho_{\rm s}\f$, then shrink the
trust region: \f$\Delta = \max \{ \beta_{\rm s} \Delta,
\Delta_{\min} \} \f$.
<li> Otherwise if \f$\rho > \rho_{\rm e}\f$ and \f$\|d\|_2 =
\Delta\f$, then expand the trust region: \f$\Delta = \min \{
\beta_{\rm e} \Delta, \Delta_{\rm max} \} \f$.
</ul>
</ul>
<B>Input Paramters</B>
The following parameters should be specified in the "Trust Region"
sublist based to the solver.
- "Direction" - Sublist of the direction parameters for the %Newton
point, passed to the NOX::Direction::Manager constructor. If this
sublist does not exist, it is created by default. Furthermore, if
"Method" is not specified in this sublist, it is added with a value of
"Newton".
- "Cauchy %Direction" - Sublist of the direction parameters for the
Cauchy point, passed to the NOX::Direction::Manager
constructor. If this sublist does not exist, it is created by
default. Furthremore, if "Method" is not specified in this
sublist, it is added with a value of "Steepest Descent" Finally,
if the sub-sublist "Steepest Descent" does not exist, it is
created and the parameter "Scaling Type" is added and set to
"Quadratic".
- "Minimum Trust Region Radius" (\f$\Delta_{\min}\f$) - Minimum allowable trust region
radius. Defaults to 1.0e-6.
- "Maximum Trust Region Radius" (\f$\Delta_{\max}\f$) - Maximum allowable trust region
radius. Defaults to 1.0e+10.
- "Minimum Improvement Ratio" (\f$\rho_{\min}\f$) - Minimum improvement ratio to accept
the step. Defaults to 1.0e-4.
- "Contraction Trigger Ratio" (\f$\rho_{\rm s}\f$) - If the improvement ratio is less than
this value, then the trust region is contracted by the amount
specified by the "Contraction Factor". Must be larger than "Minimum
Improvement Ratio". Defaults to 0.1.
- "Contraction Factor" (\f$\beta_{\rm s}\f$) - See above. Defaults to 0.25.
- "Expansion Trigger Ratio" (\f$\rho_{\rm e}\f$) - If the
improvement ratio is greater than this value, then the trust region
is contracted by the amount specified by the "Expansion
Factor". Defaults to 0.75.
- "Expansion Factor" (\f$\beta_{\rm e}\f$) - See above. Defaults to 4.0.
- "Recovery Step" - Defaults to 1.0.
- "Use Ared/Pred Ratio Calculation" (boolean) - Defaults to false. If
set to true, this option replaces the algorithm used to compute the
improvement ratio, \f$ \rho \f$, as described above. The improvement
ratio is replaced by an "Ared/Pred" sufficient decrease criteria
similar to that used in line search algorithms (see Eisenstat and
Walker, SIAM Journal on Optimization V4 no. 2 (1994) pp 393-422):
- \f$\rho = \frac{\|F(x) \| - \| F(x + d) \| }
{\| F(x) \| - \| F(x) + Jd \| } \f$
- "Solver Options" - Sublist of general solver options.
<ul>
<li> "User Defined Pre/Post Operator" is supported. See NOX::Parameter::PrePostOperator for more details.
</ul>
<B>Output Paramters</B>
A sublist for output parameters called "Output" will be created and contain the following parameters:
- "Nonlinear Iterations" - Number of nonlinear iterations
- "2-Norm or Residual" - Two-norm of final residual
\author Tammy Kolda (SNL 8950), Roger Pawlowski (SNL 9233)
*/
class TrustRegionBased : public Generic {
public:
/*!
\brief Constructor
See reset() for description.
*/
TrustRegionBased(const Teuchos::RCP<NOX::Abstract::Group>& grp,
const Teuchos::RCP<NOX::StatusTest::Generic>& tests,
const Teuchos::RCP<Teuchos::ParameterList>& params);
//! Destructor
virtual ~TrustRegionBased();
virtual void reset(const NOX::Abstract::Vector& initialGuess,
const Teuchos::RCP<NOX::StatusTest::Generic>& tests);
virtual void reset(const NOX::Abstract::Vector& initialGuess);
virtual NOX::StatusTest::StatusType getStatus();
virtual NOX::StatusTest::StatusType step();
virtual NOX::StatusTest::StatusType solve();
virtual const NOX::Abstract::Group& getSolutionGroup() const;
virtual const NOX::Abstract::Group& getPreviousSolutionGroup() const;
virtual int getNumIterations() const;
virtual const Teuchos::ParameterList& getList() const;
inline virtual Teuchos::RCP< const NOX::Abstract::Group > getSolutionGroupPtr() const {return solnPtr;};
inline virtual Teuchos::RCP< const NOX::Abstract::Group > getPreviousSolutionGroupPtr() const {return oldSolnPtr;};
inline virtual Teuchos::RCP< const Teuchos::ParameterList > getListPtr() const {return paramsPtr;};
protected:
//! Print out initialization information and calcuation the RHS.
virtual void init();
//! Print and error message and throw and error
virtual void invalid(const std::string& param, double value) const;
//! Prints the current iteration information.
virtual void printUpdate();
protected:
//! Pointer to the global data object.
Teuchos::RCP<NOX::GlobalData> globalDataPtr;
//! Printing Utils
Teuchos::RCP<NOX::Utils> utilsPtr;
//! Current solution.
Teuchos::RCP<NOX::Abstract::Group> solnPtr;
//! Previous solution pointer.
/*! We have both a pointer and a reference because we need to create
a DERIVED object and then want to have a reference to it. */
Teuchos::RCP<NOX::Abstract::Group> oldSolnPtr;
//! Current search direction.pointer.
/*! We have both a pointer and a reference because we need to create
a DERIVED object and then want to have a reference to it. */
Teuchos::RCP<NOX::Abstract::Vector> newtonVecPtr;
//! Current search direction.pointer.
/*! We have both a pointer and a reference because we need to create
a DERIVED object and then want to have a reference to it. */
Teuchos::RCP<NOX::Abstract::Vector> cauchyVecPtr;
//! Extra vector used in computations
/*! We have both a pointer and a reference because we need to create
a DERIVED object and then want to have a reference to it. */
Teuchos::RCP<NOX::Abstract::Vector> aVecPtr;
//! Extra vector used in computations
/*! We have both a pointer and a reference because we need to create
a DERIVED object and then want to have a reference to it. */
Teuchos::RCP<NOX::Abstract::Vector> bVecPtr;
//! Stopping test.
Teuchos::RCP<NOX::StatusTest::Generic> testPtr;
//! Type of check to use for status tests. See NOX::StatusTest for more details.
NOX::StatusTest::CheckType checkType;
//! Input parameters.
Teuchos::RCP<Teuchos::ParameterList> paramsPtr;
//! %Newton %Search %Direction.
Teuchos::RCP<NOX::Direction::Generic> newtonPtr;
//! Cauchy %Search %Direction.
Teuchos::RCP<NOX::Direction::Generic> cauchyPtr;
//! Radius of the trust region
double radius;
//! Minimum improvement ratio to accept step
double minRatio;
//! Initial trust region radius
double initRadius;
//! Minimum trust region radius
double minRadius;
//! Maximum trust region radius
double maxRadius;
//! ratio < alpha triggers contraction
double contractTriggerRatio;
//! ratio > beta triggers expansion
double expandTriggerRatio;
//! Expansion factor
double expandFactor;
//! Constraction factor
double contractFactor;
//! Take a step of this length in the Newton direction if the
//! trust-region search fails
double recoveryStep;
//! Value of \f$ f \f$ at current solution
double newF;
//! Value of \f$ f \f$ at previous solution
double oldF;
//! norm(xnew - xold)
double dx;
//! Number of nonlinear iterations.
int nIter;
//! %Status of nonlinear solver.
NOX::StatusTest::StatusType status;
//! Enumerated list for each direction that may be required in the Trust region computation.
enum StepType
{
//! Use the Newton direction
Newton,
//! Use the Cauchy direction
Cauchy,
//! Use the doglog direction
Dogleg
};
//! Type of step to be taken.
StepType stepType;
//! Stores a user supplied merit function if supplied in the parameter list.
Teuchos::RCP<NOX::MeritFunction::Generic> meritFuncPtr;
//! If set to true, the minimum improvement ratio condition uses an Ared/Pred approach.
bool useAredPredRatio;
//! Pointer to a user defined NOX::Abstract::PrePostOperator object.
NOX::Solver::PrePostOperator prePostOperator;
};
} // namespace Solver
} // namespace NOX
#endif
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