ROL
|
Equality constraints c_i(x) = 0, where: c1(x) = x1^2+x2^2+x3^2+x4^2+x5^2 - 10 c2(x) = x2*x3-5*x4*x5 c3(x) = x1^3 + x2^3 + 1. More...
#include <ROL_SimpleEqConstrained.hpp>
Public Member Functions | |
void | value (Vector< Real > &c, const Vector< Real > &x, Real &tol) |
Evaluate the constraint operator \(c:\mathcal{X} \rightarrow \mathcal{C}\) at \(x\). More... | |
void | applyJacobian (Vector< Real > &jv, const Vector< Real > &v, const Vector< Real > &x, Real &tol) |
Apply the constraint Jacobian at \(x\), \(c'(x) \in L(\mathcal{X}, \mathcal{C})\), to vector \(v\). More... | |
void | applyAdjointJacobian (Vector< Real > &ajv, const Vector< Real > &v, const Vector< Real > &x, Real &tol) |
Apply the adjoint of the the constraint Jacobian at \(x\), \(c'(x)^* \in L(\mathcal{C}^*, \mathcal{X}^*)\), to vector \(v\). More... | |
void | applyAdjointHessian (Vector< Real > &ahuv, const Vector< Real > &u, const Vector< Real > &v, const Vector< Real > &x, Real &tol) |
Apply the adjoint of the constraint Hessian at \(x\), \(c''(x)^* \in L(L(\mathcal{C}^*, \mathcal{X}^*), \mathcal{X}^*)\), to vector \(v\) in direction \(u\). More... | |
![]() | |
virtual std::vector< Real > | solveAugmentedSystem (Vector< Real > &v1, Vector< Real > &v2, const Vector< Real > &b1, const Vector< Real > &b2, const Vector< Real > &x, Real &tol) |
Approximately solves the augmented system
\[ \begin{pmatrix} I & c'(x)^* \\ c'(x) & 0 \end{pmatrix} \begin{pmatrix} v_{1} \\ v_{2} \end{pmatrix} = \begin{pmatrix} b_{1} \\ b_{2} \end{pmatrix} \] where \(v_{1} \in \mathcal{X}\), \(v_{2} \in \mathcal{C}^*\), \(b_{1} \in \mathcal{X}^*\), \(b_{2} \in \mathcal{C}\), \(I : \mathcal{X} \rightarrow \mathcal{X}^*\) is an identity operator, and \(0 : \mathcal{C}^* \rightarrow \mathcal{C}\) is a zero operator. More... | |
virtual void | applyPreconditioner (Vector< Real > &pv, const Vector< Real > &v, const Vector< Real > &x, Real &tol) |
Apply a constraint preconditioner at \(x\), \(P(x) \in L(\mathcal{C}, \mathcal{C}^*)\), to vector \(v\). Ideally, this preconditioner satisfies the following relationship:
\[ \left[c'(x) \circ R \circ c'(x)^* \circ P(x)\right] v = v \,, \] where R is the appropriate Riesz map in \(L(\mathcal{X}^*, \mathcal{X})\). It is used by the solveAugmentedSystem method. More... | |
virtual void | update (const Vector< Real > &x, bool flag=true, int iter=-1) |
Update constraint functions. x is the optimization variable, flag = true if optimization variable is changed, iter is the outer algorithm iterations count. | |
virtual bool | isFeasible (const Vector< Real > &v) |
Check if the vector, v, is feasible. | |
void | activate (void) |
Turn on constraints. | |
void | deactivate (void) |
Turn off constraints. | |
bool | isActivated (void) |
Check if constraints are on. | |
virtual std::vector < std::vector< Real > > | checkApplyJacobian (const Vector< Real > &x, const Vector< Real > &v, const Vector< Real > &jv, const bool printToScreen=true, const int numSteps=ROL_NUM_CHECKDERIV_STEPS) |
Finite-difference check for the constraint Jacobian application. | |
virtual std::vector < std::vector< Real > > | checkApplyAdjointJacobian (const Vector< Real > &x, const Vector< Real > &v, const Vector< Real > &c, const bool printToScreen=true, const int numSteps=ROL_NUM_CHECKDERIV_STEPS) |
Finite-difference check for the application of the adjoint of constraint Jacobian. | |
virtual std::vector < std::vector< Real > > | checkApplyAdjointHessian (const Vector< Real > &x, const Vector< Real > &u, const Vector< Real > &v, const bool printToScreen=true, const int numSteps=ROL_NUM_CHECKDERIV_STEPS) |
Finite-difference check for the application of the adjoint of constraint Hessian. | |
Equality constraints c_i(x) = 0, where: c1(x) = x1^2+x2^2+x3^2+x4^2+x5^2 - 10 c2(x) = x2*x3-5*x4*x5 c3(x) = x1^3 + x2^3 + 1.
Definition at line 448 of file ROL_SimpleEqConstrained.hpp.
|
inlinevirtual |
Evaluate the constraint operator \(c:\mathcal{X} \rightarrow \mathcal{C}\) at \(x\).
[out] | c | is the result of evaluating the constraint operator at x; a constraint-space vector |
[in] | x | is the constraint argument; an optimization-space vector |
[in,out] | tol | is a tolerance for inexact evaluations; currently unused |
On return, \(\mathsf{c} = c(x)\), where \(\mathsf{c} \in \mathcal{C}\), \(\mathsf{x} \in \mathcal{X}\).
Implements ROL::EqualityConstraint< Real >.
Definition at line 453 of file ROL_SimpleEqConstrained.hpp.
|
inlinevirtual |
Apply the constraint Jacobian at \(x\), \(c'(x) \in L(\mathcal{X}, \mathcal{C})\), to vector \(v\).
[out] | jv | is the result of applying the constraint Jacobian to v at x; a constraint-space vector |
[in] | v | is an optimization-space vector |
[in] | x | is the constraint argument; an optimization-space vector |
[in,out] | tol | is a tolerance for inexact evaluations; currently unused |
On return, \(\mathsf{jv} = c'(x)v\), where \(v \in \mathcal{X}\), \(\mathsf{jv} \in \mathcal{C}\).
The default implementation is a finite-difference approximation.
Reimplemented from ROL::EqualityConstraint< Real >.
Definition at line 478 of file ROL_SimpleEqConstrained.hpp.
|
inlinevirtual |
Apply the adjoint of the the constraint Jacobian at \(x\), \(c'(x)^* \in L(\mathcal{C}^*, \mathcal{X}^*)\), to vector \(v\).
[out] | ajv | is the result of applying the adjoint of the constraint Jacobian to v at x; a dual optimization-space vector |
[in] | v | is a dual constraint-space vector |
[in] | x | is the constraint argument; an optimization-space vector |
[in,out] | tol | is a tolerance for inexact evaluations; currently unused |
On return, \(\mathsf{ajv} = c'(x)^*v\), where \(v \in \mathcal{C}^*\), \(\mathsf{ajv} \in \mathcal{X}^*\).
The default implementation is a finite-difference approximation.
Reimplemented from ROL::EqualityConstraint< Real >.
Definition at line 515 of file ROL_SimpleEqConstrained.hpp.
|
inlinevirtual |
Apply the adjoint of the constraint Hessian at \(x\), \(c''(x)^* \in L(L(\mathcal{C}^*, \mathcal{X}^*), \mathcal{X}^*)\), to vector \(v\) in direction \(u\).
[out] | ahuv | is the result of applying the adjoint of the constraint Hessian to v at x in direction u; a dual optimization-space vector |
[in] | u | is the direction vector; a dual constraint-space vector |
[in] | v | is a dual optimization-space vector |
[in] | x | is the constraint argument; an optimization-space vector |
[in,out] | tol | is a tolerance for inexact evaluations; currently unused |
On return, \( \mathsf{ahuv} = c''(x)^*(u,v) \), where \(u \in \mathcal{C}^*\), \(v \in \mathcal{X}^*\), and \(\mathsf{ahuv} \in \mathcal{X}^*\).
The default implementation is a finite-difference approximation based on the adjoint Jacobian.
Reimplemented from ROL::EqualityConstraint< Real >.
Definition at line 553 of file ROL_SimpleEqConstrained.hpp.