ConstrainedOptPack Namespace Reference

Namespaces
	QPSchurPack

Classes
class	DecompositionSystem
	This class abstracts a decomposition choice for the quasi-range space Y and null space Z matrices for a linearly independent set of columns of Gc. More...
class	DecompositionSystemCoordinate
	Coordinate variable reduction subclass. More...
class	DecompositionSystemOrthogonal
	Orthogonal variable reduction subclass. More...
class	DecompositionSystemTester
	Testing class for DecompositionSystem interface. More...
class	DecompositionSystemTesterSetOptions
	Set options for DecompositionSystemTester from an OptionsFromStream object. More...
class	DecompositionSystemVarReduct
	Specialization of DecompositionSystem for variable reduction decompositions. More...
class	DecompositionSystemVarReductImp
	Specialization node implementation subclass of DecompositionSystem for variable reduction decompositions. More...
class	DecompositionSystemVarReductPerm
	Specialization interface of DecompositonSystem that allows basis permutations. More...
class	DecompositionSystemVarReductPermStd
	Concreate subclass of DecompositionSystemVarReductPerm that uses an aggregate DecompostionSystemVarReductImp object. More...
class	DirectLineSearch_Strategy
	Abstract strategy interface for 1D line searches {abstract}. More...
class	DirectLineSearchArmQuad_Strategy
	Performs a line search using the Armijo condition and uses quadratic interpolation to select each new alpha. More...
class	DirectLineSearchArmQuad_StrategySetOptions
	Set options for DirectLineSearchArmQuad_Strategy from a OptionsFromStream object. More...
class	MeritFuncCalc
	Abstract iterface for n-D merit functions {abstract}. More...
class	MeritFuncCalc1D
	Abstracts a 1D merit function {abstract}. More...
class	MeritFuncCalc1DQuadratic
	Adds the ability to compute phi(alpha) at alpha of a given set of vectors. More...
class	MeritFuncCalcNLE
	Adds the ability to compute phi(c(x)) at x directly instead of having to compute c first. This class uses an aggregate NLP to perform the computations of c(x). More...
class	MeritFuncCalcNLP
	Adds the ability to compute phi(f(x),c(x),h(x)) at x directly instead of having to compute f, c and h first. This class uses an aggregate NLP to perform the computations of f(x) c(x) and h(x). More...
class	MeritFuncNLE
	Base class for all merit functions for systems of NonLinear Equations (NLE) {abstract}. More...
class	MeritFuncNLESqrResid
	A merit function for the square of the constriant values. More...
class	MeritFuncNLP
	Base class for all merit functions for NonLinear Programs (NLP) {abstract}. More...
class	MeritFuncNLPDirecDeriv
	This class provides a mix-in interface for allowing subclass merit functions to compute the directional 1D derivative at a base point. More...
class	MeritFuncNLPL1
	The L1 merit function. More...
class	MeritFuncNLPModL1
	The modified L1 merit function using different penatly parameters for each constriant. More...
class	MeritFuncPenaltyParam
	This class provides interface for setting and retrieving a penalty parameter that many merit functions use {abstract}. More...
class	MeritFuncPenaltyParams
	This class provides interface for setting and retrieving a penalty parameter that many merit functions use {abstract}. More...
class	MatrixDecompRangeOrthog
	Matrix subclass for variable reduction orthogonal matrix R = Gc(:,con_decomp)'*Y. More...
class	MatrixGenBanded
	Matrix subclass for general (possibly singular) banded matrices. More...
class	MatrixHessianRelaxed
	Represents a symmetric Hessian matrix with a relaxation variable added. More...
class	MatrixHessianSuperBasic
	Matrix class that represents a hessian matrix where only the super submatrix for the super basic variables need be nonsingular. More...
class	MatrixHessianSuperBasicInitDiagonal
	Matrix class that adds the ability to initialize to a diagonal to a MatrixHessainSuperBasic object. More...
class	MatrixIdentConcat
	Matrix class for a matrix vertically concatonated with an identity matrix {abstract}. More...
class	MatrixIdentConcatStd
	Concrete implementation class for a matrix vertically concatonated with an identity matrix. More...
class	MatrixKKTFullSpaceRelaxed
	Implementation of a KKT matrix factorized in the full space. More...
class	MatrixSymAddDelBunchKaufman
	This class maintains the factorization of symmetric indefinite matrix using a Bunch & Kaufman factorization. More...
class	MatrixSymAddDelUpdateableWithOpNonsingular
	Interface for updating a symmetric matrix and its factorization by adding and deleting rows and columns and preforming operations with it. More...
class	MatrixSymHessianRelaxNonSing
	Matrix class for non-singular Hessian matrix augmented with a terms for "Big M" relaxation variables. More...
class	MatrixSymIdentitySerial
	Matrix class for a serial scaled identity matrix. More...
class	MatrixSymPosDefBandedChol
	Matrix subclass for banded symmetric positive definite matrices and their Cholesky factors. More...
class	MatrixSymPosDefInvCholFactor
	Implementation of MatrixOp abstract interface for SymInvCholMatrix. More...
class	MatrixSymPosDefLBFGS
	Implementation of limited Memory BFGS matrix for arbitrary vector spaces. More...
class	MatrixVarReductImplicit
	Implements D = - inv(C) * N for a variable reduction projection. More...
class	VariableBoundsTester
	Tests that a set of variables are within their bounds. More...
class	VariableBoundsTesterSetOptions
	Set options for VariableBoundsTester from an OptionsFromStream object. More...
class	QPSchur
	Solves a Quadratic Program with a dual QP method using a schur complement factorization. More...
class	QPSchurInitKKTSystemHessianFixedFree
	Implementation of initial KKT system using the Hessian for the free variables only. More...
class	QPSchurInitKKTSystemHessianFull
	Implementation of initial KKT system for all variables initially free and Ko = G. More...
class	QPSchurInitKKTSystemHessianRelaxed
	Implementation of initial KKT system where all original variables are free and all the relaxation variables are fixed. More...
class	QPSchurInitKKTSystemHessianSuperBasic
	Implementation of initial KKT system for all variables initially fixed and free where #Ko = B_RR#. More...
class	QPSolverRelaxed
	Solves Quadratic Programs (QPs) of several different forms while allowing a relaxation of the constraints. More...
class	QPSolverRelaxedQPKWIK
	Solves Quadratic Programming (QP) problem using the primal-dual active-set solver QPKWIK. More...
class	QPSolverRelaxedQPOPTSOL
	Node base clase for the primal QP solvers QPOPT and QPSOL. More...
class	QPSolverRelaxedQPSchur
	Solves Quadratic Programming (QP) problems using QPSchur. More...
class	QPSolverRelaxedQPSchurSetOptions
	Set options for QPSolverRelaxedQPSchur from an OptionsFromStream object. More...
class	QPSolverRelaxedTester
	Tests the optimality conditions of the output from a QPSolverRelaxed object. More...
class	QPSolverRelaxedTesterSetOptions
	Set options for QPSolverRelaxedTester from an OptionsFromStream object. More...
class	QPSolverStats
	Class for storing statistics about a run of a (active set?) QP solver. More...

Enumerations
enum	EBounds { FREE, UPPER, LOWER, EQUALITY }
	Bounds type. More...

Functions
value_type	min (value_type v1, value_type v2)
value_type	max (value_type v1, value_type v2)
void	initialize_Q_R_Q_X (size_type n_R, size_type n_X, const size_type i_x_free[], const size_type i_x_fixed[], bool test_setup, size_type Q_R_row_i[], size_type Q_R_col_j[], GenPermMatrixSlice *Q_R, size_type Q_X_row_i[], size_type Q_X_col_j[], GenPermMatrixSlice *Q_X)
	Initialize GenPermMatrixSlice mapping matrices for Q_R and Q_X. More...
void	print_vector_change_stats (const DVectorSlice &x, const char x_name[], const DVectorSlice &d, const char d_name[], std::ostream &out)
	Compute statistics for change in a vector and output to a stream. More...
void	vector_change_stats (const DVectorSlice &x, const DVectorSlice &d, value_type *max_term, size_type *max_k, value_type *min_term, size_type *min_k, value_type *av_term)
	Compute statistics for change in a vector. More...
std::string	toString (const QPSolverStats::ESolutionType &solution_type)

Compute the minimum absolute value of the given
Lagrange multipliers. A small Lagrange multiplier indicates degeneracy.
value_type	min_abs (const DVectorSlice &mu)
	Minimum |mu(i)|. More...
value_type	min_abs (const SpVectorSlice &mu)
	Minimum |mu(i)|. More...

Enumeration Type Documentation

enum ConstrainedOptPack::EBounds

Bounds type.

Enumerator
FREE
UPPER
LOWER
EQUALITY

Definition at line 53 of file ConstrainedOptPack_Types.hpp.

Function Documentation

value_type ConstrainedOptPack::min ( value_type  v1, value_type  v2  )

inline

Definition at line 51 of file ConstrainedOptPack_DirectLineSearchArmQuad_Strategy.cpp.

value_type ConstrainedOptPack::max ( value_type  v1, value_type  v2  )

inline

Definition at line 54 of file ConstrainedOptPack_DirectLineSearchArmQuad_Strategy.cpp.

ConstrainedOptPack::value_type ConstrainedOptPack::min_abs

(

const DVectorSlice &

mu

)

Minimum |mu(i)|.

Definition at line 55 of file ConstrainedOptPack_ComputeMinMult.cpp.

ConstrainedOptPack::value_type ConstrainedOptPack::min_abs

(

const SpVectorSlice &

mu

)

Minimum |mu(i)|.

Definition at line 66 of file ConstrainedOptPack_ComputeMinMult.cpp.

void ConstrainedOptPack::initialize_Q_R_Q_X	(	size_type	n_R,
		size_type	n_X,
		const size_type	i_x_free[],
		const size_type	i_x_fixed[],
		bool	test_setup,
		size_type	Q_R_row_i[],
		size_type	Q_R_col_j[],
		GenPermMatrixSlice *	Q_R,
		size_type	Q_X_row_i[],
		size_type	Q_X_col_j[],
		GenPermMatrixSlice *	Q_X
	)

Initialize GenPermMatrixSlice mapping matrices for Q_R and Q_X.

Parameters

n_R	[in] Number of free variables
n_X	[in] Number of fixed variables
i_x_free	[in] array (length n_R) of indices of free variables. If n_R == 0 then i_x_free can be NULL. It is allowed for i_x_free == NULL in which case it is determined to from i_x_fixed[] (if n_X > 0) and i_x_free is assumed to be sorted in assending order.
i_x_fixed	[in] array (length n_X) of indices of fixed variables. If n_X == 0 then i_x_fixed can be NULL.
test_setup	[in] If true then i_x_free[] and i_x_fixed[] will be validated and if not okay then an exception will be thown.
Q_R_row_i	[out] array (length n_R) of row indices for Q_R. If n_R == 0 or i_x_free == NULL and it is known that i_x_fixed[l] > n_R, for l = 0...n_X-1, then Q_R_row_i can be NULL and will not be accessed. If Q_R_row_i != NULL then it will always be set. This array will be sorted in assending order on output if it is set.
Q_R_col_j	[out] array (length n_R) of column indices for Q_R. Q_R_col_j can be NULL when Q_R_row_i is NULL. If this array turns out to be sorted then Q_R will be set to Q_R->ordered_by() == BY_ROW_AND_COL
Q_R	[out] GenPermMatixSlice object initialized with Q_R_row_i and Q_R_col_j. If n_R == 0 then Q_R will be initialized to (n_X by 0). If it turns out that i_x_free == NULL and Q_R has the identity matrix as its leading nonzero matrix, then Q_R->is_identity() will be true on output. In any case Q_R->ordered_by() will be BY_ROW or BY_ROW_AND_COL on output.
Q_X_row_i	[out] array (length n_X) of row indices for Q_X. If n_X == 0 then Q_X_row_i can be NULL and will not be accessed.
Q_X_col_j	[out] array (length n_X) of column indices for Q_X If n_X == 0 then Q_X_col_j can be NULL and will not be accessed. If this array turns out to be sorted then Q_X will be set to Q_X->ordered_by() == BY_ROW_AND_COL
Q_X	[out] GenPermMatixSlice object initialized with Q_X_row_i and Q_X_col_j If n_X == 0 then Q_X will be initialized to (n_X by 0.) On output Q_X->ordered_by() will be BY_ROW or BY_ROW_AND_COL.

Definition at line 47 of file ConstrainedOptPack_initialize_Q_R_Q_X.cpp.

void ConstrainedOptPack::print_vector_change_stats	(	const DVectorSlice &	x,
		const char	x_name[],
		const DVectorSlice &	d,
		const char	d_name[],
		std::ostream &	out
	)

Compute statistics for change in a vector and output to a stream.

Calls the function vector_change_stats(x,d,max_term,max_k,min_term,min_k ,av_term) then produces the following output to the given stream.

max(|d(i)|/(1+|x(i)|)) => |d(max_k)|/(1+|x(max_k)|) = max_term \ min(|d(i)|/(1+|x(i)|)) => |d(min_k)|/(1+|x(min_k)|) = min_term \ average(|d(i)|/(1+|x(i)|)) = av_term \

Note that above the names x and d are replaced with their input names #x_name# and #d_name# and max_term, max_k etc. are replaced with their computed values.

Definition at line 45 of file ConstrainedOptPack_print_vector_change_stats.cpp.

void ConstrainedOptPack::vector_change_stats	(	const DVectorSlice &	x,
		const DVectorSlice &	d,
		value_type *	max_term,
		size_type *	max_k,
		value_type *	min_term,
		size_type *	min_k,
		value_type *	av_term
	)

Compute statistics for change in a vector.

Given two vectors x and d where we wish to generate statistics for the update x+d this function computes the following quantitines:

max( |d(i)|/(1+|x(i)|), i=1...n ) => #max_k# = k, #max_term# = |d(k)|/(1+|x(k)|) <= 1\ min( |d(i)|/(1+|x(i)|), i=1...n ) => #min_k# = k, #min_term# = |d(k)|/(1+|x(k)|)#\ #average( |d(i)|/(1+|x(i)|), i=1...10 )# => #av_term#\

The purpose of generating these satistics is to determine by how much x+d differs from x.

If |d(i)|/|x(i)| < mach_eps with x(i) > 0 then we know that d(i) will be lost when added to x(i) so x(i) + d(i) == x(i).

Definition at line 49 of file ConstrainedOptPack_vector_change_stats.cpp.

std::string ConstrainedOptPack::toString ( const QPSolverStats::ESolutionType &  solution_type )

inline

Definition at line 146 of file ConstrainedOptPack_QPSolverStats.hpp.