OSInstance Class Reference

The in-memory representation of an OSiL instance.. More...

#include <OSInstance.h>

Collaboration diagram for OSInstance:

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List of all members.

Public Member Functions
	OSInstance ()
	The OSInstance class constructor.
	~OSInstance ()
	The OSInstance class destructor.
bool	IsEqual (OSInstance *that)
	A function to check for the equality of two objects.
std::string	getInstanceName ()
	Get instance name.
std::string	getInstanceSource ()
	Get instance source.
std::string	getInstanceDescription ()
	Get instance description.
std::string	getInstanceCreator ()
	Get instance fileCreator.
std::string	getInstanceLicence ()
	Get instance licence.
int	getVariableNumber ()
	Get number of variables.
std::string *	getVariableNames ()
	Get variable names.
char *	getVariableTypes ()
	Get variable initial values.
int	getNumberOfIntegerVariables ()
	getNumberOfIntegerVariables
int	getNumberOfBinaryVariables ()
	getNumberOfBinaryVariables
int	getNumberOfSemiContinuousVariables ()
	getNumberOfSemiContinuousVariables
int	getNumberOfSemiIntegerVariables ()
	getNumberOfSemiIntegerVariables
int	getNumberOfStringVariables ()
	getNumberOfStringVariables
double *	getVariableLowerBounds ()
	Get variable lower bounds.
double *	getVariableUpperBounds ()
	Get variable upper bounds.
int	getObjectiveNumber ()
	Get number of objectives.
std::string *	getObjectiveNames ()
	Get objective names.
std::string *	getObjectiveMaxOrMins ()
	Get objective maxOrMins.
int *	getObjectiveCoefficientNumbers ()
	Get objective coefficient number.
double *	getObjectiveConstants ()
	Get objective constants.
double *	getObjectiveWeights ()
	Get objective weights.
SparseVector **	getObjectiveCoefficients ()
	Get objective coefficients.
double **	getDenseObjectiveCoefficients ()
	getDenseObjectiveCoefficients.
int	getConstraintNumber ()
	Get number of constraints.
std::string *	getConstraintNames ()
	Get constraint names.
double *	getConstraintLowerBounds ()
	Get constraint lower bounds.
double *	getConstraintUpperBounds ()
	Get constraint upper bounds.
double *	getConstraintConstants ()
	Get constraint constants.
char *	getConstraintTypes ()
	Get constraint types.
int	getLinearConstraintCoefficientNumber ()
	Get number of specified (usually nonzero) linear constraint coefficient values.
bool	getLinearConstraintCoefficientMajor ()
	Get whether the constraint coefficients is in column major (true) or row major (false).
SparseMatrix *	getLinearConstraintCoefficientsInColumnMajor ()
	Get linear constraint coefficients in column major.
SparseMatrix *	getLinearConstraintCoefficientsInRowMajor ()
	Get linear constraint coefficients in row major.
int	getNumberOfQuadraticTerms ()
	Get the number of specified (usually nonzero) qTerms in the quadratic coefficients.
QuadraticTerms *	getQuadraticTerms ()
	Get all the quadratic terms in the instance.
int *	getQuadraticRowIndexes ()
	Get the indexes of rows which have a quadratic term.
int	getNumberOfQuadraticRowIndexes ()
	Get the number of rows which have a quadratic term.
int	getNumberOfNonlinearExpressions ()
	Get number of nonlinear expressions.
Nl **	getNonlinearExpressions ()
	Get the pointers to the roots of all expression trees.
ScalarExpressionTree *	getNonlinearExpressionTree (int rowIdx)
	Get the expression tree for a given row index.
ScalarExpressionTree *	getNonlinearExpressionTreeMod (int rowIdx)
	Get the expression tree for a given row index for the modified expression trees (quadratic terms added).
std::vector< ExprNode * >	getNonlinearExpressionTreeInPostfix (int rowIdx)
	Get the postfix tokens for a given row index.
std::vector< ExprNode * >	getNonlinearExpressionTreeModInPostfix (int rowIdx)
	Get the postfix tokens for a given row index for the modified Expression Tree (quadratic terms added).
std::vector< ExprNode * >	getNonlinearExpressionTreeInPrefix (int rowIdx)
	Get the prefix tokens for a given row index.
std::string	getNonlinearExpressionTreeInInfix (int rowIdx)
	Get the infix representation for a given row (or objective function) index.
std::vector< ExprNode * >	getNonlinearExpressionTreeModInPrefix (int rowIdx)
	Get the prefix tokens for a given row index for the modified Expression Tree (quadratic terms added).
int	getNumberOfNonlinearObjectives ()
int	getNumberOfNonlinearConstraints ()
std::map< int, ScalarExpressionTree * >	getAllNonlinearExpressionTrees ()
std::map< int, ScalarExpressionTree * >	getAllNonlinearExpressionTreesMod ()
int *	getNonlinearExpressionTreeIndexes ()
	Get all the nonlinear expression tree indexes, i.e., indexes of rows (objectives or constraints) that contain nonlinear expressions.
int	getNumberOfNonlinearExpressionTreeIndexes ()
	Get the number of unique nonlinear expression tree indexes.
int *	getNonlinearExpressionTreeModIndexes ()
	Get all the nonlinear expression tree indexes, i.e., indexes of rows (objectives or constraints) that contain nonlinear expressions after modifying the expression tree to contain quadratic terms.
int	getNumberOfNonlinearExpressionTreeModIndexes ()
	Get the number of unique nonlinear expression tree indexes after modifying the expression tree to contain quadratic terms.
int	getMatrixNumber ()
	Get the number of matrices.
ENUM_MATRIX_TYPE	getMatrixType (int n)
	Get the matrix type.
ENUM_MATRIX_SYMMETRY	getMatrixSymmetry (int n)
	Get the matrix symmetry.
int	getNumberOfColumnsForMatrix (int n)
	Get the number of blocks in the matrix.
int	getNumberOfRowsForMatrix (int n)
	Get the number of rows in the matrix.
int	getNumberOfValuesForMatrix (int n)
	Get the number of (nonzero) values in the matrix.
std::string	getMatrixName (int n)
	Get the name of the matrix.
bool	matrixHasBase (int n)
	Several tools to parse the constructor list of a matrix.
bool	matrixHasElements (int n)
bool	matrixHasTransformations (int n)
bool	matrixHasBlocks (int n)
int	getNumberOfElementConstructors (int n)
int	getNumberOfTransformationConstructors (int n)
int	getNumberOfBlocksConstructors (int n)
OSMatrix *	getMatrix (int n)
	Get the list of constructors of the matrix.
GeneralSparseMatrix *	getMatrixCoefficientsInColumnMajor (int n)
	Get the (nonzero) elements of the matrix in column major form.
GeneralSparseMatrix *	getMatrixCoefficientsInRowMajor (int n)
	Get the (nonzero) elements of the matrix in row major form.
GeneralSparseMatrix *	getMatrixBlockInColumnMajorForm (int n, int columnIdx, int rowIdx)
	Get the (nonzero) elements of the matrix in symmetric block form.
int	getNumberOfMatrixVariables ()
	Get the number of matrix variables.
int	getNumberOfMatrixObjectives ()
	Get the number of matrix objectives.
int	getNumberOfMatrixConstraints ()
	Get the number of matrix constraints.
int	getNumberOfMatrixExpressions ()
	Get the number of matrix-valued expressions.
MatrixExpression **	getMatrixExpressions ()
	Get the pointers to the roots of all matrix expression trees.
MatrixExpressionTree *	getMatrixExpressionTree (int rowIdx)
	Get the matrix expression tree for a given row index.
std::vector< ExprNode * >	getMatrixExpressionTreeInPostfix (int rowIdx)
	Get the postfix tokens for a given row index.
std::vector< ExprNode * >	getMatrixExpressionTreeModInPostfix (int rowIdx)
	Get the postfix tokens for a given row index for the modified Expression Tree (quadratic terms added).
std::vector< ExprNode * >	getMatrixExpressionTreeInPrefix (int rowIdx)
	Get the prefix tokens for a given row index.
std::string	getMatrixExpressionTreeInInfix (int rowIdx)
	Get the infix representation for a given row (or objective function) index.
std::map< int, MatrixExpressionTree * >	getAllMatrixExpressionTrees ()
std::map< int, MatrixExpressionTree * >	getAllMatrixExpressionTreesMod ()
int *	getMatrixExpressionTreeIndexes ()
	Get all the matrix expression tree indexes, i.e.
int	getNumberOfMatrixExpressionTreeIndexes ()
	Get the number of unique matrix expression tree indexes.
std::string	getTimeDomainFormat ()
	Get the format of the time domain ("stages"/"interval").
int	getTimeDomainStageNumber ()
	Get the number of stages that make up the time domain.
std::string *	getTimeDomainStageNames ()
	Get the names of the stages (NULL or empty string ("") if a stage has not been given a name.
int *	getTimeDomainStageNumberOfVariables ()
	Get the number of variables contained in each time stage.
int *	getTimeDomainStageNumberOfConstraints ()
	Get the number of constraints contained in each time stage.
int *	getTimeDomainStageNumberOfObjectives ()
	Get the number of objectives contained in each time stage.
int **	getTimeDomainStageVarList ()
	Get the list of variables in each stage.
int **	getTimeDomainStageConList ()
	Get the list of constraints in each stage.
int **	getTimeDomainStageObjList ()
	Get the list of objectives in each stage.
double	getTimeDomainIntervalStart ()
	Get the start for the time domain interval.
double	getTimeDomainIntervalHorizon ()
	Get the horizon for the time domain interval.
bool	setInstanceName (std::string name)
	set the instance name.
bool	setInstanceSource (std::string source)
	set the instance source.
bool	setInstanceDescription (std::string description)
	set the instance description.
bool	setInstanceCreator (std::string fileCreator)
	set the instance creator.
bool	setInstanceLicence (std::string licence)
	set the instance licence.
bool	setVariableNumber (int number)
	set the number of variables.
bool	addVariable (int index, std::string name, double lowerBound, double upperBound, char type)
	add a variable.
bool	setVariables (int number, std::string *names, double *lowerBounds, double *upperBounds, char *types)
	set all the variable related elements.
bool	setObjectiveNumber (int number)
	set the number of objectives.
bool	addObjective (int index, std::string name, std::string maxOrMin, double constant, double weight, SparseVector *objectiveCoefficients)
	add an objective.
bool	setObjectives (int number, std::string *names, std::string *maxOrMins, double *constants, double *weights, SparseVector **objectitiveCoefficients)
	set all the objectives related elements.
bool	setConstraintNumber (int number)
	set the number of constraints.
bool	addConstraint (int index, std::string name, double lowerBound, double upperBound, double constant)
	add a constraint.
bool	setConstraints (int number, std::string *names, double *lowerBounds, double *upperBounds, double *constants)
	set all the constraint related elements.
bool	setLinearConstraintCoefficients (int numberOfValues, bool isColumnMajor, double *values, int valuesBegin, int valuesEnd, int *indexes, int indexesBegin, int indexesEnd, int *starts, int startsBegin, int startsEnd)
	set linear constraint coefficients
bool	copyLinearConstraintCoefficients (int numberOfValues, bool isColumnMajor, double *values, int valuesBegin, int valuesEnd, int *indexes, int indexesBegin, int indexesEnd, int *starts, int startsBegin, int startsEnd)
	copy linear constraint coefficients: perform a deep copy of the sparse matrix
bool	setNumberOfQuadraticTerms (int nq)
	set the number of quadratic terms
bool	setQuadraticCoefficients (int number, int *rowIndexes, int *varOneIndexes, int *varTwoIndexes, double *coefficients, int begin, int end)
	set quadratic coefficients into the QuadraticCoefficients->qTerm data structure
bool	setQuadraticTermsInNonlinearExpressions (int number, int *rowIndexes, int *varOneIndexes, int *varTwoIndexes, double *coefficients)
	set quadratic terms in nonlinearExpressions
bool	setNonlinearExpressions (int nexpr, Nl **root)
	set nonlinear expressions
bool	setMatrixNumber (int number)
	set the number of matrices
bool	addMatrix (int index, std::string name, int numberOfRows, int numberOfColumns, ENUM_MATRIX_SYMMETRY symmetry, ENUM_MATRIX_TYPE matrixType, unsigned int inumberOfChildren, MatrixNode **m_mChildren)
	add a matrix.
bool	setConeNumber (int number)
	set the number of cones
bool	addCone (int index, int numberOfRows, int numberOfColumns, ENUM_CONE_TYPE coneType, std::string name, int numberOfOtherIndexes=0, int *otherIndexes=NULL)
	add a cone.
bool	addCone (int index, int numberOfRows, int numberOfColumns, ENUM_CONE_TYPE coneType, std::string name, int numberOfComponents, int *components, int numberOfOtherIndexes=0, int *otherIndexes=NULL)
	add a cone.
bool	addCone (int index, int numberOfRows, int numberOfColumns, ENUM_CONE_TYPE coneType, std::string name, int referenceIdx, int numberOfOtherIndexes=0, int *otherIndexes=NULL)
	add a cone.
bool	addCone (int index, int numberOfRows, int numberOfColumns, ENUM_CONE_TYPE coneType, std::string name, std::string semidefiniteness, int numberOfOtherIndexes=0, int *otherIndexes=NULL)
	add a cone.
bool	addCone (int index, int numberOfRows, int numberOfColumns, ENUM_CONE_TYPE coneType, std::string name, int distortionMatrixIdx, double normFactor, int axisDirection, int numberOfOtherIndexes=0, int *otherIndexes=NULL)
	add a cone.
bool	addCone (int index, int numberOfRows, int numberOfColumns, ENUM_CONE_TYPE coneType, std::string name, int distortionMatrixIdx, double normFactor, int firstAxisDirection, int secondAxisDirection, int numberOfOtherIndexes=0, int *otherIndexes=NULL)
	add a cone.
bool	addCone (int index, int numberOfRows, int numberOfColumns, ENUM_CONE_TYPE coneType, std::string name, int distortionMatrixIdx, double normFactor, int axisDirection, double pNorm, int numberOfOtherIndexes=0, int *otherIndexes=NULL)
	add a cone.
bool	addCone (int index, int numberOfRows, int numberOfColumns, ENUM_CONE_TYPE coneType, std::string name, int maxDegree, int numberOfUB, double *ub, int numberOfLB, double *lb, int numberOfOtherIndexes=0, int *otherIndexes=NULL)
	add a cone.
std::string	printModel ()
	Print the infix representation of the problem.
std::string	printModel (int rowIdx)
	Print the infix representation of the row (which could be an an objective function row) indexed by rowIdx.
bool	initializeNonLinearStructures ()
	Initialize the data structures for the nonlinear API.
double	calculateFunctionValue (int idx, double *x, bool new_x)
	Calculate the function value for function (constraint or objective) indexed by idx.
double *	calculateAllConstraintFunctionValues (double *x, double *objLambda, double *conLambda, bool new_x, int highestOrder)
	Calculate all of the constraint function values.
double *	calculateAllConstraintFunctionValues (double *x, bool new_x)
	Calculate all of the constraint function values, we are overloading this function and this version of the method will not use any AD and will evaluate function values from the OS Expression Tree.
double *	calculateAllObjectiveFunctionValues (double *x, double *objLambda, double *conLambda, bool new_x, int highestOrder)
	Calculate all of the objective function values.
double *	calculateAllObjectiveFunctionValues (double *x, bool new_x)
	Calculate all of the objective function values, we are overloading this function and this version of the method will not use any AD and will evaluate function values from the OS Expression Tree.
SparseJacobianMatrix *	calculateAllConstraintFunctionGradients (double *x, double *objLambda, double *conLambda, bool new_x, int highestOrder)
	Calculate the gradient of all constraint functions.
SparseVector *	calculateConstraintFunctionGradient (double *x, double *objLambda, double *conLambda, int idx, bool new_x, int highestOrder)
	Calculate the gradient of the constraint function indexed by idx.
SparseVector *	calculateConstraintFunctionGradient (double *x, int idx, bool new_x)
	Calculate the gradient of the constraint function indexed by idx this function is overloaded.
double **	calculateAllObjectiveFunctionGradients (double *x, double *objLambda, double *conLambda, bool new_x, int highestOrder)
	Calculate the gradient of all objective functions.
double *	calculateObjectiveFunctionGradient (double *x, double *objLambda, double *conLambda, int objIdx, bool new_x, int highestOrder)
	Calculate the gradient of the objective function indexed by objIdx.
double *	calculateObjectiveFunctionGradient (double *x, int objIdx, bool new_x)
	Calculate the gradient of the objective function indexed by objIdx this function is overloaded.
SparseHessianMatrix *	calculateLagrangianHessian (double *x, double *objLambda, double *conLambda, bool new_x, int highestOrder)
	Calculate the Hessian of the Lagrangian Expression Tree This method will build the CppAD expression tree for only the first iteration Use this method on if the value of x does not affect the operations sequence.
SparseHessianMatrix *	calculateHessian (double *x, int idx, bool new_x)
	Calculate the Hessian of a constraint or objective function.
bool	getSparseJacobianFromColumnMajor ()
bool	getSparseJacobianFromRowMajor ()
ScalarExpressionTree *	getLagrangianExpTree ()
std::map< int, int >	getAllNonlinearVariablesIndexMap ()
SparseHessianMatrix *	getLagrangianHessianSparsityPattern ()
bool	addQTermsToExressionTree ()
bool	addQTermsToExpressionTree ()
	This method adds quadratic terms into the array of expression trees.
SparseJacobianMatrix *	getJacobianSparsityPattern ()
void	duplicateExpressionTreesMap ()
	duplicate the map of expression trees.
bool	createOSADFun (std::vector< double > vdX)
	Create the a CppAD Function object: this is a function where the domain is the set of variables for the problem and the range is the objective function plus constraints.
std::vector< double >	forwardAD (int p, std::vector< double > vdX)
	Perform an AD forward sweep.
std::vector< double >	reverseAD (int p, std::vector< double > vdlambda)
	Perform an AD reverse sweep.
int	getADSparsityHessian ()
	end revised AD code
bool	getIterateResults (double *x, double *objLambda, double *conLambda, bool new_x, int highestOrder)
	end revised AD code
bool	getZeroOrderResults (double *x, double *objLambda, double *conLambda)
	Calculate function values.
bool	getFirstOrderResults (double *x, double *objLambda, double *conLambda)
	Calculate first derivatives.
bool	getSecondOrderResults (double *x, double *objLambda, double *conLambda)
	Calculate second derivatives.
bool	initForAlgDiff ()
	This should be called by nonlinear solvers using callback functions.
bool	initObjGradients ()
	This should be called by initForAlgDiff().
bool	setTimeDomain (std::string format)
	This sets the format of the time domain ("stages"/"interval"/"none").
bool	setTimeDomainStages (int number, std::string *names)
	This sets the number (and optionally names) of the time stages.
bool	setTimeDomainStageVariablesOrdered (int numberOfStages, int *numberOfVariables, int *startIdx)
	This sets the variables associated with each time domain stage in temporal order.
bool	setTimeDomainStageVariablesUnordered (int numberOfStages, int *numberOfVariables, int **varIndex)
	This sets the variables associated with each time domain stage in srbitrary order.
bool	setTimeDomainStageConstraintsOrdered (int numberOfStages, int *numberOfConstraints, int *startIdx)
	This sets the constraints associated with each time domain stage in temporal order.
bool	setTimeDomainStageConstraintsUnordered (int numberOfStages, int *numberOfConstraints, int **conIndex)
	This sets the constraints associated with each time domain stage in srbitrary order.
bool	setTimeDomainStageObjectivesOrdered (int numberOfStages, int *numberOfObjectives, int *startIdx)
	This sets the objectives associated with each time domain stage in temporal order.
bool	setTimeDomainStageObjectivesUnordered (int numberOfStages, int *numberOfObjectives, int **varIndex)
	This sets the objectives associated with each time domain stage in arbitrary order.
bool	setTimeDomainInterval (double start, double horizon)
	This sets the start and end of the time interval.
	OSInstance ()
	The OSInstance class constructor.
	~OSInstance ()
	The OSInstance class destructor.
std::string	getInstanceName ()
	Get instance name.
std::string	getInstanceSource ()
	Get instance source.
std::string	getInstanceDescription ()
	Get instance description.
int	getVariableNumber ()
	Get variable number.
std::string *	getVariableNames ()
	Get variable names.
char *	getVariableTypes ()
	Get variable initial values.
int	getNumberOfIntegerVariables ()
	getNumberOfIntegerVariables
int	getNumberOfBinaryVariables ()
	getNumberOfBinaryVariables
double *	getVariableLowerBounds ()
	Get variable lower bounds.
double *	getVariableUpperBounds ()
	Get variable upper bounds.
int	getObjectiveNumber ()
	Get objective number.
std::string *	getObjectiveNames ()
	Get objective names.
std::string *	getObjectiveMaxOrMins ()
	Get objective maxOrMins.
int *	getObjectiveCoefficientNumbers ()
	Get objective coefficient number.
double *	getObjectiveConstants ()
	Get objective constants.
double *	getObjectiveWeights ()
	Get objective weights.
SparseVector **	getObjectiveCoefficients ()
	Get objective coefficients.
double **	getDenseObjectiveCoefficients ()
	getDenseObjectiveCoefficients.
int	getConstraintNumber ()
	Get constraint number.
std::string *	getConstraintNames ()
	Get constraint names.
double *	getConstraintLowerBounds ()
	Get constraint lower bounds.
double *	getConstraintUpperBounds ()
	Get constraint upper bounds.
char *	getConstraintTypes ()
	Get constraint types.
int	getLinearConstraintCoefficientNumber ()
	Get number of specified (usually nonzero) linear constraint coefficient values.
bool	getLinearConstraintCoefficientMajor ()
	Get whether the constraint coefficients is in column major (true) or row major (false).
SparseMatrix *	getLinearConstraintCoefficientsInColumnMajor ()
	Get linear constraint coefficients in column major.
SparseMatrix *	getLinearConstraintCoefficientsInRowMajor ()
	Get linear constraint coefficients in row major.
int	getNumberOfQuadraticTerms ()
	Get the number of specified (usually nonzero) qTerms in the quadratic coefficients.
QuadraticTerms *	getQuadraticTerms ()
	Get all the quadratic terms in the instance.
int *	getQuadraticRowIndexes ()
	Get the indexes of rows which have a quadratic term.
int	getNumberOfQuadraticRowIndexes ()
	Get the number of rows which have a quadratic term.
int	getNumberOfNonlinearExpressions ()
	Get number of nonlinear expressions.
OSExpressionTree *	getNonlinearExpressionTree (int rowIdx)
	Get the expression tree for a given row index.
OSExpressionTree *	getNonlinearExpressionTreeMod (int rowIdx)
	Get the expression tree for a given row index for the modified expression trees (quadratic terms added).
std::vector< OSnLNode * >	getNonlinearExpressionTreeInPostfix (int rowIdx)
	Get the postfix tokens for a given row index.
std::vector< OSnLNode * >	getNonlinearExpressionTreeModInPostfix (int rowIdx)
	Get the postfix tokens for a given row index for the modified Expression Tree (quadratic terms added).
std::vector< OSnLNode * >	getNonlinearExpressionTreeInPrefix (int rowIdx)
	Get the prefix tokens for a given row index.
std::vector< OSnLNode * >	getNonlinearExpressionTreeModInPrefix (int rowIdx)
	Get the prefix tokens for a given row index for the modified Expression Tree (quadratic terms added).
int	getNumberOfNonlinearObjectives ()
int	getNumberOfNonlinearConstraints ()
std::map< int, OSExpressionTree * >	getAllNonlinearExpressionTrees ()
std::map< int, OSExpressionTree * >	getAllNonlinearExpressionTreesMod ()
int *	getNonlinearExpressionTreeIndexes ()
	Get all the nonlinear expression tree indexes, i.e.
int	getNumberOfNonlinearExpressionTreeIndexes ()
	Get the number of unique Nonlinear expression tree indexes.
int *	getNonlinearExpressionTreeModIndexes ()
	Get all the nonlinear expression tree indexes, i.e.
int	getNumberOfNonlinearExpressionTreeModIndexes ()
	Get the number of unique Nonlinear expression tree indexes after modifying the expression tree to contain quadratic terms.
std::string	getTimeDomainFormat ()
	Get the format of the time domain ("stages"/"interval").
int	getTimeDomainStageNumber ()
	Get the number of stages that make up the time domain.
std::string *	getTimeDomainStageNames ()
	Get the names of the stages (NULL or empty string ("") if a stage has not been given a name.
int *	getTimeDomainStageNumberOfVariables ()
	Get the number of variables contained in each time stage.
int *	getTimeDomainStageNumberOfConstraints ()
	Get the number of constraints contained in each time stage.
int *	getTimeDomainStageNumberOfObjectives ()
	Get the number of objectives contained in each time stage.
int **	getTimeDomainStageVarList ()
	Get the list of variables in each stage.
int **	getTimeDomainStageConList ()
	Get the list of constraints in each stage.
int **	getTimeDomainStageObjList ()
	Get the list of objectives in each stage.
double	getTimeDomainIntervalStart ()
	Get the start for the time domain interval.
double	getTimeDomainIntervalHorizon ()
	Get the horizon for the time domain interval.
bool	setInstanceSource (std::string source)
	set the instance source.
bool	setInstanceDescription (std::string description)
	set the instance description.
bool	setInstanceName (std::string name)
	set the instance name.
bool	setVariableNumber (int number)
	set the variable number.
bool	addVariable (int index, std::string name, double lowerBound, double upperBound, char type)
	add a variable.
bool	setVariables (int number, std::string *names, double *lowerBounds, double *upperBounds, char *types)
	set all the variable related elements.
bool	setObjectiveNumber (int number)
	set the objective number.
bool	addObjective (int index, std::string name, std::string maxOrMin, double constant, double weight, SparseVector *objectiveCoefficients)
	add an objective.
bool	setObjectives (int number, std::string *names, std::string *maxOrMins, double *constants, double *weights, SparseVector **objectitiveCoefficients)
	set all the objectives related elements.
bool	setConstraintNumber (int number)
	set the constraint number.
bool	addConstraint (int index, std::string name, double lowerBound, double upperBound, double constant)
	add a constraint.
bool	setConstraints (int number, std::string *names, double *lowerBounds, double *upperBounds, double *constants)
	set all the constraint related elements.
bool	setLinearConstraintCoefficients (int numberOfValues, bool isColumnMajor, double *values, int valuesBegin, int valuesEnd, int *indexes, int indexesBegin, int indexesEnd, int *starts, int startsBegin, int startsEnd)
	set linear constraint coefficients
bool	setQuadraticTerms (int number, int *rowIndexes, int *varOneIndexes, int *varTwoIndexes, double *coefficients, int begin, int end)
	set quadratic terms
bool	setQuadraticTermsInNonlinearExpressions (int number, int *rowIndexes, int *varOneIndexes, int *varTwoIndexes, double *coefficients)
	set quadratic terms in nonlinearExpressions
bool	initializeNonLinearStructures ()
	Initialize the data structures for the nonlinear API.
double	calculateFunctionValue (int idx, double *x, bool new_x)
	Calculate the function value for function (constraint or objective) indexed by idx.
double *	calculateAllConstraintFunctionValues (double *x, double *objLambda, double *conLambda, bool new_x, int highestOrder)
	Calculate all of the constraint function values.
double *	calculateAllConstraintFunctionValues (double *x, bool new_x)
	Calculate all of the constraint function values, we are overloading this function and this version of the method will not use any AD and will evaluate function values from the OS Expression Tree.
double *	calculateAllObjectiveFunctionValues (double *x, double *objLambda, double *conLambda, bool new_x, int highestOrder)
	Calculate all of the objective function values.
double *	calculateAllObjectiveFunctionValues (double *x, bool new_x)
	Calculate all of the objective function values, we are overloading this function and this version of the method will not use any AD and will evaluate function values from the OS Expression Tree.
SparseJacobianMatrix *	calculateAllConstraintFunctionGradients (double *x, double *objLambda, double *conLambda, bool new_x, int highestOrder)
	Calculate the gradient of all constraint functions.
SparseVector *	calculateConstraintFunctionGradient (double *x, double *objLambda, double *conLambda, int idx, bool new_x, int highestOrder)
	Calculate the gradient of the constraint function indexed by idx.
SparseVector *	calculateConstraintFunctionGradient (double *x, int idx, bool new_x)
	Calculate the gradient of the constraint function indexed by idx this function is overloaded.
double **	calculateAllObjectiveFunctionGradients (double *x, double *objLambda, double *conLambda, bool new_x, int highestOrder)
	Calculate the gradient of all objective functions.
double *	calculateObjectiveFunctionGradient (double *x, double *objLambda, double *conLambda, int objIdx, bool new_x, int highestOrder)
	Calculate the gradient of the objective function indexed by objIdx.
double *	calculateObjectiveFunctionGradient (double *x, int objIdx, bool new_x)
	Calculate the gradient of the objective function indexed by objIdx this function is overloaded.
SparseHessianMatrix *	calculateLagrangianHessian (double *x, double *objLambda, double *conLambda, bool new_x, int highestOrder)
	Calculate the Hessian of the Lagrangian Expression Tree This method will build the CppAD expression tree for only the first iteration Use this method on if the value of x does not affect the operations sequence.
SparseHessianMatrix *	calculateHessian (double *x, int idx, bool new_x)
	Calculate the Hessian of a constraint or objective function.
bool	getSparseJacobianFromColumnMajor ()
bool	getSparseJacobianFromRowMajor ()
OSExpressionTree *	getLagrangianExpTree ()
std::map< int, int >	getAllNonlinearVariablesIndexMap ()
SparseHessianMatrix *	getLagrangianHessianSparsityPattern ()
bool	addQTermsToExressionTree ()
SparseJacobianMatrix *	getJacobianSparsityPattern ()
void	duplicateExpressionTreesMap ()
	duplicate the map of expression trees.
bool	createOSADFun (std::vector< double > vdX)
	Create the a CppAD Function object: this is a function where the domain is the set of variables for the problem and the range is the objective function plus constraints.
std::vector< double >	forwardAD (int p, std::vector< double > vdX)
	Perform an AD forward sweep.
std::vector< double >	reverseAD (int p, std::vector< double > vdlambda)
	Perform an AD reverse sweep.
int	getADSparsityHessian ()
	end revised AD code
bool	getIterateResults (double *x, double *objLambda, double *conLambda, bool new_x, int highestOrder)
	end revised AD code
bool	getZeroOrderResults (double *x, double *objLambda, double *conLambda)
	Calculate function values.
bool	getFirstOrderResults (double *x, double *objLambda, double *conLambda)
	Calculate first derivatives.
bool	getSecondOrderResults (double *x, double *objLambda, double *conLambda)
	Calculate second derivatives.
bool	initForAlgDiff ()
	This should be called by nonlinear solvers using callback functions.
bool	initObjGradients ()
	This should be called by initForAlgDiff().
bool	setTimeDomain (std::string format)
	This sets the format of the time domain ("stages"/"interval"/"none").
bool	setTimeDomainStages (int number, std::string *names)
	This sets the number (and optionally names) of the time stages.
bool	setTimeDomainStageVariablesOrdered (int numberOfStages, int *numberOfVariables, int *startIdx)
	This sets the variables associated with each time domain stage in temporal order.
bool	setTimeDomainStageVariablesUnordered (int numberOfStages, int *numberOfVariables, int **varIndex)
	This sets the variables associated with each time domain stage in srbitrary order.
bool	setTimeDomainStageConstraintsOrdered (int numberOfStages, int *numberOfConstraints, int *startIdx)
	This sets the constraints associated with each time domain stage in temporal order.
bool	setTimeDomainStageConstraintsUnordered (int numberOfStages, int *numberOfConstraints, int **conIndex)
	This sets the constraints associated with each time domain stage in srbitrary order.
bool	setTimeDomainStageObjectivesOrdered (int numberOfStages, int *numberOfObjectives, int *startIdx)
	This sets the objectives associated with each time domain stage in temporal order.
bool	setTimeDomainStageObjectivesUnordered (int numberOfStages, int *numberOfObjectives, int **varIndex)
	This sets the objectives associated with each time domain stage in arbitrary order.
bool	setTimeDomainInterval (double start, double horizon)
	This sets the start and end of the time interval.
Public Attributes
GeneralFileHeader *	instanceHeader
	the instanceHeader is implemented as a general file header object to allow sharing of classes between schemas
InstanceData *	instanceData
	A pointer to an InstanceData object.
bool	bVariablesModified
	bVariablesModified is true if the variables data has been modified.
bool	bObjectivesModified
	bObjectivesModified is true if the objective function data has been modified.
bool	bConstraintsModified
	bConstraintsModified is true if the constraints data has been modified.
bool	bAMatrixModified
	bAMatrixModified is true if the A matrix data has been modified.
CppAD::ADFun< double > *	Fad
	F is a CppAD function the range space is the objective + constraints functions, x is the domeain space.
bool	bUseExpTreeForFunEval
	bUseExpTreeForFunEval is set to true if you wish to use the OS Expression Tree for function evaluations instead of AD -- false by default.
InstanceHeader *	instanceHeader
	A pointer to an InstanceHeader object.
Private Member Functions
bool	processVariables ()
	process variables.
bool	processObjectives ()
	process objectives.
bool	processConstraints ()
	process constraints.
bool	processLinearConstraintCoefficients ()
	process linear constraint coefficients.
bool	processMatrices ()
	process matrices.
bool	processVariables ()
	process variables.
bool	processObjectives ()
	process objectives.
bool	processConstraints ()
	process constraints.
bool	processLinearConstraintCoefficients ()
	process linear constraint coefficients.
Private Attributes
std::string	m_sInstanceName
	------- data items for InstanceHeader -------
std::string	m_sInstanceSource
	m_sInstanceSource holds the instance source.
std::string	m_sInstanceDescription
	m_sInstanceDescription holds the instance description.
std::string	m_sInstanceCreator
	m_sInstanceSource holds the instance source.
std::string	m_sInstanceLicence
	m_sInstanceDescription holds the instance fileCreator info.
bool	m_bProcessVariables
	------- data items for Variables -------
int	m_iVariableNumber
	m_iVariableNumber holds the variable number.
int	m_iNumberOfIntegerVariables
	m_iNumberOfIntegerVariables holds the number of integer variables.
int	m_iNumberOfBinaryVariables
	m_iNumberOfBinaryVariables holds the number of binary variables.
int	m_iNumberOfSemiContinuousVariables
	m_iNumberOfSemiContinuousVariables holds the number of semi-continuous variables.
int	m_iNumberOfSemiIntegerVariables
	m_iNumberOfSemiIntegerVariables holds the number of semi-integer variables.
int	m_iNumberOfStringVariables
	m_iNumberOfStringVariables holds the number of string-valued variables.
std::string *	m_msVariableNames
	m_msVariableNames holds an array of variable names.
char *	m_mcVariableTypes
	m_mcVariableTypes holds a char array of variable types (default = 'C').
double *	m_mdVariableLowerBounds
	m_mdVariableLowerBounds holds a double array of variable lower bounds (default = 0.0).
double *	m_mdVariableUpperBounds
	m_mdVariableUpperBounds holds a double array of variable upper bounds (default = INF).
bool	m_bProcessObjectives
	------- data items for Objectives -------
int	m_iObjectiveNumber
	m_iObjectiveNumber is the number of objective functions.
int	m_iObjectiveNumberNonlinear
	m_iObjectiveNumber is the number of objective functions with a nonlinear term.
std::string *	m_msObjectiveNames
	m_msObjectiveNames holds an array of objective names.
std::string *	m_msMaxOrMins
	m_msMaxOrMins holds a std::string array of objective maxOrMins ("max" or "min").
int *	m_miNumberOfObjCoef
	m_miNumberOfObjCoef holds an integer array of number of objective coefficients (default = 0).
double *	m_mdObjectiveConstants
	m_mdObjectiveConstants holds an array of objective constants (default = 0.0).
double *	m_mdObjectiveWeights
	m_mdObjectiveWeights holds an array of objective weights (default = 1.0).
SparseVector **	m_mObjectiveCoefficients
	m_mObjectiveCoefficients holds an array of objective coefficients, one set of objective coefficients for each objective.
bool	m_bGetDenseObjectives
	m_bGetDenseObjectives holds whether the dense objective functions are processed.
double **	m_mmdDenseObjectiveCoefficients
	m_mmdDenseObjectiveCoefficients holds an array of pointers, each pointer points to a vector of dense objective function coefficients
bool	m_bProcessConstraints
	------- data items for Constraints -------
int	m_iConstraintNumber
	m_iConstraintNumber is the number of constraints.
int	m_iConstraintNumberNonlinear
	m_iConstraintNumberNonlinear is the number of constraints that have a nonlinear term.
std::string *	m_msConstraintNames
	m_msConstraintNames holds an array of constraint names.
double *	m_mdConstraintLowerBounds
	m_mdConstraintLowerBounds holds an array of constraint lower bounds (default = -INF).
double *	m_mdConstraintUpperBounds
	m_mdConstraintUpperBounds holds an array of constraint upper bounds (default = INF).
double *	m_mdConstraintConstants
	m_mdConstraintConstants holds an array of constraint constants (default = 0.0).
char *	m_mcConstraintTypes
	m_mcConstraintTypes holds a char array of constraint types (R for range; L for <=; G for >=; E for =; U for unconstrained)
bool	m_bProcessLinearConstraintCoefficients
	------- data items for linear constraint coefficients -------
int	m_iLinearConstraintCoefficientNumber
	m_iLinearConstraintCoefficientNumber holds the number of specified (usually nonzero) linear constraint coefficient values.
bool	m_bColumnMajor
	m_bColumnMajor holds whether the linear constraint coefficients are stored in column major (if m_bColumnMajor = true) or row major.
SparseMatrix *	m_linearConstraintCoefficientsInColumnMajor
	m_linearConstraintCoefficientsInColumnMajor holds the standard three-array data structure for linear constraint coefficients (starts, indexes and values) in column major.
SparseMatrix *	m_linearConstraintCoefficientsInRowMajor
	m_linearConstraintCoefficientsInRowMajor holds the standard three-array data structure for linear constraint coefficients (starts, indexes and values) in row major.
int	m_iNumberOfQuadraticRowIndexes
	------- data items for quadratic coefficients -------
bool	m_bQuadraticRowIndexesProcessed
	m_bQuadraticRowIndexesProcessed is true if getQuadraticRowIndexes() has been called.
int *	m_miQuadRowIndexes
	m_miQuadRowIndexes is an integer pointer to the distinct row indexes with a quadratic term.
bool	m_bProcessQuadraticTerms
	m_bProcessQuadraticTerms holds whether the quadratic terms are processed.
int	m_iQuadraticTermNumber
	m_iQuadraticTermNumber holds the number of specified (usually nonzero) qTerms in the quadratic coefficients.
QuadraticTerms *	m_quadraticTerms
	m_quadraticTerms holds the data structure for all the quadratic terms in the instance.
bool	m_bQTermsAdded
	m_bQTermsAdded is true if we added the quadratic terms to the expression tree
int	m_iNumberOfNonlinearExpressionTreeIndexes
	------- data items for nonlinear expressions -------
bool	m_bNonlinearExpressionTreeIndexesProcessed
	m_bNonlinearExpressionTreeIndexesProcessed is true if getNonlinearExpressionTreeIndexes() has been called.
int *	m_miNonlinearExpressionTreeIndexes
	m_miNonlinearExpressionTreeIndexes is an integer pointer to the distinct rows indexes in the nonlinear expression tree map.
int	m_iNumberOfNonlinearExpressionTreeModIndexes
	m_iNumberOfNonlinearExpressionTreeModIndexes holds the number of distinct rows and objectives with nonlinear terms including quadratic terms added to the nonlinear expression trees.
bool	m_bNonlinearExpressionTreeModIndexesProcessed
	m_bNonlinearExpressionTreeModIndexesProcessed is true if getNonlinearExpressionTreeModIndexes has been called.
int *	m_miNonlinearExpressionTreeModIndexes
	m_miNonlinearExpressionTreeModIndexes is an integer pointer to the distinct rows indexes in the modified expression tree map.
bool	m_binitForAlgDiff
	------- data items for automatic differentiation -------
unsigned int	m_iNumberOfNonlinearVariables
	m_iNumberOfNonlinearVariables is the number of variables that appear in a nonlinear expression.
bool	m_bProcessNonlinearExpressions
	m_bProcessNonlinearExpressions holds whether the nonlinear expressions are processed.
int	m_iNonlinearExpressionNumber
	m_iNonlinearExpressionNumber holds the number of nonlinear expressions.
int *	m_miNonlinearExpressionIndexes
	m_miNonlinearExpressionIndexes holds an integer array of nonlinear expression indexes, negative indexes correspond to objectives.
bool	m_bProcessExpressionTrees
	m_bProcessExpressionTrees is true if the expression trees have been processed.
bool	m_bProcessExpressionTreesMod
	m_bProcessExpressionTreesMod is true if the modified expression trees have been processed.
double *	m_mdConstraintFunctionValues
	m_mdConstraintFunctionValues holds a double array of constraint function values -- the size of the array is equal to getConstraintNumber().
double *	m_mdObjectiveFunctionValues
	m_mdObjectiveFunctionValues holds a double array of objective function values -- the size of the array is equal to getObjectiveNumber().
int	m_iJacValueSize
	m_iJacValueSize is the number of nonzero partial derivates in the Jacobian.
int *	m_miJacStart
	m_miJacStart holds a int array of starts for the Jacobian matrix in sparse form (row major).
int *	m_miJacIndex
	m_miJacIndex holds a int array of variable indices for the Jacobian matrix in sparse form (row major).
double *	m_mdJacValue
	m_mdJacValue holds a double array of partial derivatives for the Jacobian matrix in sparse form (row major).
int *	m_miJacNumConTerms
	m_miJacNumConTerms holds a int array of the number of constant terms (gradient does not change) for the Jacobian matrix in sparse form (row major).
SparseJacobianMatrix *	m_sparseJacMatrix
	m_sparseJacMatrix is the Jacobian matrix stored in sparse matrix format
int	m_iHighestTaylorCoeffOrder
	m_iHighestTaylorCoeffOrder is the order of highest calculated Taylor coefficient
std::map< int, ScalarExpressionTree * >	m_mapExpressionTrees
	m_mapExpressionTrees holds a hash map of scalar-valued expression tree pointers.
std::map< int, int >	m_mapOSADFunRangeIndex
	m_mapOSADFunRangeIndex is an inverse of the previous map.
std::map< int, MatrixExpressionTree * >	m_mapMatrixExpressionTrees
	m_mapMatrixExpressionTrees holds a hash map of matrix-valued expression tree pointers.
ScalarExpressionTree *	m_LagrangianExpTree
	m_LagrangianExpTree is an ScalarExpressionTree object that is the expression tree for the Lagrangian function.
bool	m_bLagrangianExpTreeCreated
	m_bLagrangianHessionCreated is true if a Lagrangian function for the Hessian has been created
SparseHessianMatrix *	m_LagrangianSparseHessian
	m_LagrangianSparseHessian is the Hessian Matrix of the Lagrangian function in sparse format
bool	m_bLagrangianSparseHessianCreated
	m_bLagrangianSparseHessianCreated is true if the sparse Hessian Matrix for the Lagrangian was created
std::map< int, int >	m_mapAllNonlinearVariablesIndex
	m_mapAllNonlinearVariablesIndexMap is a map of the variables in the Lagrangian function
int *	m_miNonLinearVarsReverseMap
	m_miNonLinearVarsReverseMap maps the nonlinear variable number back into the original variable space
bool	m_bAllNonlinearVariablesIndex
	m_bAllNonlinearVariablesIndexMap is true if the map of the variables in the Lagrangian function has been constructed
std::map< int, ScalarExpressionTree * >	m_mapExpressionTreesMod
	m_mapExpressionTreesMod holds a map of expression trees, with the key being the row index and value being the expression tree representing a modification of the nonlinear expression of that row.
bool	m_bOSADFunIsCreated
	m_bOSADFunIsCreated is true if we have created the OSInstanc OSAD Function
bool	m_bCppADTapesBuilt
	is true if a CppAD Expresion Tree has been built for each row and objective with a nonlinear expression.
bool	m_bCppADMustReTape
	is true if a CppAD Expresion Tree has an expression that can change depending on the value of the input, e.g.
bool	m_bDuplicateExpressionTreesMap
	m_bDuplicateExpressionTreeMap is true if m_mapExpressionTrees was duplicated.
bool	m_bNonLinearStructuresInitialized
	m_bNonLinearStructuresInitialized is true if initializeNonLinearStructures() has been called.
bool	m_bSparseJacobianCalculated
	m_bSparseJacobianCalculated is true if getJacobianSparsityPattern() has been called.
std::map< int, std::vector < OSnLNode * > >	m_mapExpressionTreesInPostfix
	m_mapExpressionTreesInPostfix holds a hash map of expression trees in postfix format, with the key being the row index and value being the expression tree representing the nonlinear expression of that row.
int	m_iHighestOrderEvaluated
	m_iHighestOrderEvaluated is the highest order derivative of the current iterate
double **	m_mmdObjGradient
	m_mdObjGradient holds an array of pointers, each pointer points to gradient of one objective function (as a dense array of double)
std::vector< double >	m_vdX
	------- data vectors for nonlinear optimization -------
std::vector< double >	m_vdYval
	m_vdYval is a vector of function values
std::vector< bool >	m_vbLagHessNonz
	m_vbLagHessNonz is a boolean vector holding the nonzero pattern of the Lagrangian of the Hessian
std::vector< double >	m_vdYjacval
	m_vdYval is a vector equal to a column or row of the Jacobian
std::vector< double >	m_vdw
	m_vdYval is a vector of derivatives -- output from a reverse sweep
std::vector< double >	m_vdLambda
	m_vdYval is a vector of Lagrange multipliers
std::vector< double >	m_vdDomainUnitVec
	m_vdDomainUnitVec is a unit vector in the domain space
std::vector< double >	m_vdRangeUnitVec
	m_vdRangeUnitVec is a unit vector in the range space
bool	m_bProcessMatrices
	------- data items for matrices -------
int	m_iMatrixNumber
	m_iMatrixNumber holds the number of matrices
ENUM_MATRIX_SYMMETRY *	m_miMatrixSymmetry
	m_miMatrixSymmetry holds the symmetry property of each matrix.
ENUM_MATRIX_TYPE *	m_miMatrixType
	m_miMatrixType holds the type of each matrix.
int *	m_miMatrixNumberOfColumns
	m_miMatrixNumberOfColumns holds the number of columns for each matrix.
int *	m_miMatrixNumberOfRows
	m_miMatrixNumberOfRows holds the number of rows for each matrix.
std::string *	m_msMatrixNames
	m_msMatrixNames holds the names of the matrices
OSMatrix **	m_mMatrix
	m_mMatrix holds the list of constructors for each matrix.
int	m_iMatrixVarNumber
	------- data items for matrix programming -------
int	m_iMatrixObjNumber
	m_iMatrixObjNumber holds the number of matrix objectives
int	m_iMatrixConNumber
	m_iMatrixConNumber holds the number of matrix constraints
int	m_iMatrixExpressionNumber
	m_iMatrixExpressionNumber holds the number of matrix expressions
bool	m_bProcessTimeDomain
	------- data items for time domain -------
bool	m_bProcessTimeStages
	m_bProcessTimeStages holds whether the time stages have been processed.
bool	m_bProcessTimeInterval
	m_bProcessTimeInterval holds whether a time interval has been processed.
bool	m_bFiniteTimeStages
	m_bFiniteTimeStages holds whether the time domain has the form of finite (discrete) stages.
int	m_iNumberOfTimeStages
	m_iNumberOfTimeStages holds the number of discrete stages
std::string	m_sTimeDomainFormat
	m_sTimeDomainFormat holds the format ("stages"/"interval") of the time domain.
std::string *	m_msTimeDomainStageNames
	m_msTimeDomainStageNames holds the names of the time stages.
int *	m_miTimeDomainStageVariableNumber
	m_miTimeDomainStageVariableNumber holds the number of variables in each stage.
int **	m_mmiTimeDomainStageVarList
	m_mmiTimeDomainStageVarList holds the list of variables in each stage.
int *	m_miTimeDomainStageConstraintNumber
	m_miTimeDomainStageConstraintNumber holds the number of constraints in each stage.
int **	m_mmiTimeDomainStageConList
	m_mmiTimeDomainStageConList holds the list of constraints in each stage.
int *	m_miTimeDomainStageObjectiveNumber
	m_miTimeDomainStageObjectiveNumber holds the number of objectives in each stage.
int **	m_mmiTimeDomainStageObjList
	m_mmiTimeDomainStageObjList holds the list of objectives in each stage.
std::map< int, OSExpressionTree * >	m_mapExpressionTrees
	m_mapExpressionTrees holds a hash map of expression tree pointers, with the key being the row index and value being the expression tree representing the nonlinear expression of that row.
OSExpressionTree *	m_LagrangianExpTree
	m_LagrangianExpTree is an OSExpressionTree object that is the expression tree for the Lagrangian function.
std::map< int, OSExpressionTree * >	m_mapExpressionTreesMod
	m_mapExpressionTreesMod holds a map of expression trees, with the key being the row index and value being the expression tree representing a modification of the nonlinear expression of that row.

---

Detailed Description

The in-memory representation of an OSiL instance..

Remarks:

1. Elements become objects of class type (the ComplexType is the class)

2. The attributes, children of the element, and text correspond to members of the class. (Note text does not have a name and becomes .value)

3. Model groups such as choice and sequence and all correspond to arrays

1. anything specific to XML such as base64, multi, incr do not go into classes
2. The root OSnLNode of each <nl> element is called ExpressionTree
3. Root is not called osil it is called osinstance

The OSInstance class is composed of two objects: the header object instanceHeader and the data object instanceData

Remarks:

1. Elements become objects of class type (the ComplexType is the class)

2. The attributes, children of the element, and text correspond to members of the class. (Note text does not have a name and becomes .value)

3. Model groups such as choice and sequence and all correspond to arrays

1. anything specific to XML such as base64, multi, incr do not go into classes
2. The root OSnLNode of each <nl> element is called ExpressionTree
3. Root is not called osil it is called osinstance

The OSInstance class is composed of two objects: an InstanceHeader object and and InstanceData object

Definition at line 2262 of file OSInstance.h.

---

Constructor & Destructor Documentation

OSInstance::OSInstance

(

)

The OSInstance class constructor.

Definition at line 36 of file OSInstance.cpp.

OSInstance::~OSInstance

(

)

The OSInstance class destructor.

Definition at line 167 of file OSInstance.cpp.

OSInstance::OSInstance

(

)

The OSInstance class constructor.

OSInstance::~OSInstance

(

)

The OSInstance class destructor.

---

Member Function Documentation

bool OSInstance::IsEqual

(

OSInstance *

that

)

A function to check for the equality of two objects.

Definition at line 8028 of file OSInstance.cpp.

bool OSInstance::processVariables

(

)

[private]

process variables.

Returns:

true if the variables are processed.

Exceptions:

Exception

if the elements in variables are logically inconsistent.

Definition at line 2032 of file OSInstance.cpp.

bool OSInstance::processObjectives

(

)

[private]

process objectives.

Returns:

true if the objectives are processed.

Exceptions:

Exception

if the elements in objectives are logically inconsistent.

Definition at line 2189 of file OSInstance.cpp.

bool OSInstance::processConstraints

(

)

[private]

process constraints.

Returns:

true if the constraints are processed.

Exceptions:

Exception

if the elements in constraints are logically inconsistent.

Definition at line 2341 of file OSInstance.cpp.

bool OSInstance::processLinearConstraintCoefficients

(

)

[private]

process linear constraint coefficients.

Returns:

true if the linear constraint coefficients are processed.

Exceptions:

Exception

if the elements in linear constraint coefficients are logically inconsistent.

Definition at line 2454 of file OSInstance.cpp.

bool OSInstance::processMatrices

(

)

[private]

process matrices.

Returns:

true if the matrices have been processed.

Exceptions:

Exception

if the declaration of any matrix is logically inconsistent.

Definition at line 3315 of file OSInstance.cpp.

string OSInstance::getInstanceName

(

)

Get instance name.

the get() methods =================

Returns:

instance name. Null or empty std::string ("") if there is no instance name.

Definition at line 1963 of file OSInstance.cpp.

string OSInstance::getInstanceSource

(

)

Get instance source.

Returns:

instance source. Null or empty std::string ("") if there is no instance source.

Definition at line 1974 of file OSInstance.cpp.

string OSInstance::getInstanceDescription

(

)

Get instance description.

Returns:

instance description. Null or empty std::string ("") if there is no instance description.

Definition at line 1985 of file OSInstance.cpp.

string OSInstance::getInstanceCreator

(

)

Get instance fileCreator.

Returns:

instance fileCreator. Null or empty std::string ("") if there is no instance file creator.

Definition at line 1996 of file OSInstance.cpp.

string OSInstance::getInstanceLicence

(

)

Get instance licence.

Returns:

instance licence. Null or empty std::string ("") if there is no instance licence.

Definition at line 2007 of file OSInstance.cpp.

int OSInstance::getVariableNumber

(

)

Get number of variables.

Returns:

number of variables.

Definition at line 2018 of file OSInstance.cpp.

string * OSInstance::getVariableNames

(

)

Get variable names.

Returns:

a std::string array of variable names, null if no variable names.

Exceptions:

Exception

if the elements in variables are logically inconsistent.

Definition at line 2119 of file OSInstance.cpp.

char * OSInstance::getVariableTypes

(

)

Get variable initial values.

Returns:

a double array of variable initial values, null if no initial variable values.

Exceptions:

Exception

if the elements in variables are logically inconsistent. -- now deprecated Get variable initial std::string values.

Returns:

a std::string array of variable initial values, null if no initial variable std::string values.

Exceptions:

Exception

if the elements in variables are logically inconsistent. -- now deprecated Get variable types. C for Continuous B for Binary I for Integer S for String

Returns:

a char array of variable types.

Exceptions:

Exception

if the elements in variables are logically inconsistent.

Definition at line 2125 of file OSInstance.cpp.

int OSInstance::getNumberOfIntegerVariables

(

)

getNumberOfIntegerVariables

Returns:

an integer which is the number of I variables.

Definition at line 2137 of file OSInstance.cpp.

int OSInstance::getNumberOfBinaryVariables

(

)

getNumberOfBinaryVariables

Returns:

an integer which is the number of B variables.

Definition at line 2131 of file OSInstance.cpp.

int OSInstance::getNumberOfSemiContinuousVariables

(

)

getNumberOfSemiContinuousVariables

Returns:

an integer which is the number of D variables.

Definition at line 2143 of file OSInstance.cpp.

int OSInstance::getNumberOfSemiIntegerVariables

(

)

getNumberOfSemiIntegerVariables

Returns:

an integer which is the number of J variables.

Definition at line 2149 of file OSInstance.cpp.

int OSInstance::getNumberOfStringVariables

(

)

getNumberOfStringVariables

Returns:

an integer which is the number of S variables.

Definition at line 2155 of file OSInstance.cpp.

double * OSInstance::getVariableLowerBounds

(

)

Get variable lower bounds.

Returns:

a double array of variable lower bounds.

Exceptions:

Exception

if the elements in variables are logically inconsistent.

Definition at line 2161 of file OSInstance.cpp.

double * OSInstance::getVariableUpperBounds

(

)

Get variable upper bounds.

Returns:

a double array of variable upper bounds.

Exceptions:

Exception

if the elements in variables are logically inconsistent.

Definition at line 2167 of file OSInstance.cpp.

int OSInstance::getObjectiveNumber

(

)

Get number of objectives.

Returns:

number of objectives.

Definition at line 2174 of file OSInstance.cpp.

string * OSInstance::getObjectiveNames

(

)

Get objective names.

Returns:

a std::string array of objective names. Null if no objective names.

Exceptions:

Exception

if the elements in objectives are logically inconsistent.

Definition at line 2252 of file OSInstance.cpp.

string * OSInstance::getObjectiveMaxOrMins

(

)

Get objective maxOrMins.

One maxOrMin for each objective.

Returns:

a std::string array of objective maxOrMins ("max" or "min"), null if no objectives.

Exceptions:

Exception

if the elements in objectives are logically inconsistent.

Definition at line 2258 of file OSInstance.cpp.

int * OSInstance::getObjectiveCoefficientNumbers

(

)

Get objective coefficient number.

One number for each objective.

Returns:

an integer array of size of which is equal to number of objectives, each element of the array is the number of nonzero coefficients in that objective function, null if no objectives.

Exceptions:

Exception

if the elements in objectives are logically inconsistent.

Definition at line 2264 of file OSInstance.cpp.

double * OSInstance::getObjectiveConstants

(

)

Get objective constants.

One constant for each objective.

Returns:

a double array of objective constants, null if no objectives.

Exceptions:

Exception

if the elements in objectives are logically inconsistent.

Definition at line 2270 of file OSInstance.cpp.

double * OSInstance::getObjectiveWeights

(

)

Get objective weights.

One weight for each objective.

Returns:

a double array of objective weights, null if no objectives.

Exceptions:

Exception

if the elements in objectives are logically inconsistent.

Definition at line 2276 of file OSInstance.cpp.

SparseVector ** OSInstance::getObjectiveCoefficients

(

)

Get objective coefficients.

One set of objective coefficients for each objective.

See also:

org.optimizationservices.oscommon.datastructure.SparseVector

Returns:

an array of objective coefficients, null if no objectives. Each member of the array is of type ObjectiveCoefficients. The ObjectiveCoefficients class contains two arrays: variableIndexes is an integer array and values is a double array of coefficient values.

Exceptions:

Exception

if the elements in objectives are logically inconsistent.

Definition at line 2283 of file OSInstance.cpp.

double ** OSInstance::getDenseObjectiveCoefficients

(

)

getDenseObjectiveCoefficients.

Returns:

an vector of pointers, each pointer points to a dense vector of ObjectiveCoefficients.

Definition at line 2290 of file OSInstance.cpp.

int OSInstance::getConstraintNumber

(

)

Get number of constraints.

Returns:

number of constraints.

Definition at line 2327 of file OSInstance.cpp.

string * OSInstance::getConstraintNames

(

)

Get constraint names.

Returns:

a std::string array of constraint names, null if no constraint names.

Exceptions:

Exception

if the elements in constraints are logically inconsistent.

Definition at line 2406 of file OSInstance.cpp.

double * OSInstance::getConstraintLowerBounds

(

)

Get constraint lower bounds.

Returns:

a double array of constraint lower bounds, null if no constraints.

Exceptions:

Exception

if the elements in constraints are logically inconsistent.

Definition at line 2419 of file OSInstance.cpp.

double * OSInstance::getConstraintUpperBounds

(

)

Get constraint upper bounds.

Returns:

a double array of constraint upper bounds, null if no constraints.

Exceptions:

Exception

if the elements in constraints are logically inconsistent.

Definition at line 2425 of file OSInstance.cpp.

double * OSInstance::getConstraintConstants

(

)

Get constraint constants.

Returns:

a double array of constraint constants, null if no constraints.

Exceptions:

Exception

if the elements in constraints are logically inconsistent.

Definition at line 2431 of file OSInstance.cpp.

char * OSInstance::getConstraintTypes

(

)

Get constraint types.

The constraint types are not part of the OSiL schema, but they are used in solver interfaces such as OSLindoSolver.cpp.

• R for range constraint lb <= constraint <= ub
• L for less than constraint -INF <= con <= ub or con <= ub
• G for greater than constraint lb <= con <= INF or con >= lb
• E for equal to constraint lb <= con <= ub where lb = ub or con = lb (or con = ub)
• U for unconstrained constraint -INF <= con <= INF

Returns:

a char array of constraint types, null if no constraints.

Exceptions:

Exception

if the elements in constraints are logically inconsistent.

Definition at line 2413 of file OSInstance.cpp.

int OSInstance::getLinearConstraintCoefficientNumber

(

)

Get number of specified (usually nonzero) linear constraint coefficient values.

Returns:

number of specified (usually nonzero) linear constraint coefficient values.

Definition at line 2438 of file OSInstance.cpp.

bool OSInstance::getLinearConstraintCoefficientMajor

(

)

Get whether the constraint coefficients is in column major (true) or row major (false).

Returns:

whether the constraint coefficients is in column major (true) or row major (false).

Exceptions:

Exception

if the elements in linear constraint coefficients are logically inconsistent.

Definition at line 2518 of file OSInstance.cpp.

SparseMatrix * OSInstance::getLinearConstraintCoefficientsInColumnMajor

(

)

Get linear constraint coefficients in column major.

Returns:

a sparse matrix representation of linear constraint coefficients in column major, null if no linear constraint coefficients.

Exceptions:

Exception

if the elements in linear constraint coefficients are logically inconsistent.

See also:

org.optimizationservices.oscommon.datastructure.SparseMatrix

Definition at line 2524 of file OSInstance.cpp.

SparseMatrix * OSInstance::getLinearConstraintCoefficientsInRowMajor

(

)

Get linear constraint coefficients in row major.

Returns:

a sparse matrix representation of linear constraint coefficients in row major, null if no linear constraint coefficients.

Exceptions:

Exception

if the elements in linear constraint coefficients are logically inconsistent.

See also:

org.optimizationservices.oscommon.datastructure.SparseMatrix

Definition at line 2544 of file OSInstance.cpp.

int OSInstance::getNumberOfQuadraticTerms

(

)

Get the number of specified (usually nonzero) qTerms in the quadratic coefficients.

Returns:

qTerm number.

Definition at line 2565 of file OSInstance.cpp.

QuadraticTerms * OSInstance::getQuadraticTerms

(

)

Get all the quadratic terms in the instance.

Returns:

the QuadraticTerms data structure for all quadratic terms in the instance, null if no quadratic terms. The QuadraticTerms contains four arrays: rowIndexes, varOneIndexes, varTwoIndexes, coefficients.

Exceptions:

Exception

if the elements in quadratic coefficients are logically inconsistent.

See also:

org.optimizationservices.oscommon.datastructure.QuadraticTerms

Definition at line 2579 of file OSInstance.cpp.

int * OSInstance::getQuadraticRowIndexes

(

)

Get the indexes of rows which have a quadratic term.

Returns:

an integer pointer to the row indexes of rows with quadratic terms, objectives functions have index < 0 NULL if there are no quadratic terms.

Definition at line 2620 of file OSInstance.cpp.

int OSInstance::getNumberOfQuadraticRowIndexes

(

)

Get the number of rows which have a quadratic term.

Returns:

an integer which is the number of distinct rows (including obj) with quadratic terms,

Definition at line 2614 of file OSInstance.cpp.

int OSInstance::getNumberOfNonlinearExpressions

(

)

Get number of nonlinear expressions.

Returns:

the number of nonlinear expressions.

Definition at line 2656 of file OSInstance.cpp.

Nl ** OSInstance::getNonlinearExpressions

(

)

Get the pointers to the roots of all expression trees.

Returns:

an array of pointers to Nl objects

Definition at line 2670 of file OSInstance.cpp.

ScalarExpressionTree * OSInstance::getNonlinearExpressionTree

(

int

rowIdx

)

Get the expression tree for a given row index.

Returns:

an expression tree

Definition at line 2761 of file OSInstance.cpp.

ScalarExpressionTree * OSInstance::getNonlinearExpressionTreeMod

(

int

rowIdx

)

Get the expression tree for a given row index for the modified expression trees (quadratic terms added).

Returns:

an expression tree

Definition at line 2773 of file OSInstance.cpp.

std::vector< ExprNode * > OSInstance::getNonlinearExpressionTreeInPostfix

(

int

rowIdx

)

Get the postfix tokens for a given row index.

Returns:

a vector of pointers to ExprNodes in postfix, if rowIdx does not index a row with a nonlinear term throw an exception

Remarks:

The root node of the expression tree is of type OSnLNode

Definition at line 2785 of file OSInstance.cpp.

std::vector< ExprNode * > OSInstance::getNonlinearExpressionTreeModInPostfix

(

int

rowIdx

)

Get the postfix tokens for a given row index for the modified Expression Tree (quadratic terms added).

Returns:

a vector of pointers to ExprNodes in postfix, if rowIdx does not index a row with a nonlinear term throw an exception

Definition at line 3146 of file OSInstance.cpp.

std::vector< ExprNode * > OSInstance::getNonlinearExpressionTreeInPrefix

(

int

rowIdx

)

Get the prefix tokens for a given row index.

Returns:

a vector of pointers to ExprNodes in prefix, if rowIdx does not index a row with a nonlinear term throw an exception

Definition at line 3172 of file OSInstance.cpp.

std::string OSInstance::getNonlinearExpressionTreeInInfix

(

int

rowIdx

)

Get the infix representation for a given row (or objective function) index.

Parameters:

rowIdx

is the index of the row we want to express in infix.

Returns:

a string representation of the tree, if rowIdx does not index a row with a nonlinear term throw an exception

Definition at line 2809 of file OSInstance.cpp.

std::vector< ExprNode * > OSInstance::getNonlinearExpressionTreeModInPrefix

(

int

rowIdx

)

Get the prefix tokens for a given row index for the modified Expression Tree (quadratic terms added).

Returns:

a vector of pointers to ExprNodes in prefix, if rowIdx does not index a row with a nonlinear term throw an exception

Definition at line 3196 of file OSInstance.cpp.

int OSInstance::getNumberOfNonlinearObjectives

(

)

Returns:

the number of Objectives with a nonlinear term

Definition at line 2753 of file OSInstance.cpp.

int OSInstance::getNumberOfNonlinearConstraints

(

)

Returns:

the number of Constraints with a nonlinear term

Definition at line 2746 of file OSInstance.cpp.

std::map< int, ScalarExpressionTree * > OSInstance::getAllNonlinearExpressionTrees

(

)

Returns:

a map: the key is the row index and the value is the corresponding expression tree

Remarks:

If there are several expressions in a single row, this method combines them by adding OSnLPlus nodes

Definition at line 3221 of file OSInstance.cpp.

std::map< int, ScalarExpressionTree * > OSInstance::getAllNonlinearExpressionTreesMod

(

)

Returns:

a map: the key is the row index and the value is the corresponding expression tree

Definition at line 3290 of file OSInstance.cpp.

int * OSInstance::getNonlinearExpressionTreeIndexes

(

)

Get all the nonlinear expression tree indexes, i.e., indexes of rows (objectives or constraints) that contain nonlinear expressions.

Returns:

a pointer to an integer array of nonlinear expression tree indexes.

Definition at line 2687 of file OSInstance.cpp.

int OSInstance::getNumberOfNonlinearExpressionTreeIndexes

(

)

Get the number of unique nonlinear expression tree indexes.

Returns:

the number of unique nonlinear expression tree indexes.

Definition at line 2681 of file OSInstance.cpp.

int * OSInstance::getNonlinearExpressionTreeModIndexes

(

)

Get all the nonlinear expression tree indexes, i.e., indexes of rows (objectives or constraints) that contain nonlinear expressions after modifying the expression tree to contain quadratic terms.

Returns:

a pointer to an integer array of nonlinear expression tree indexes (including quadratic terms).

Definition at line 2720 of file OSInstance.cpp.

int OSInstance::getNumberOfNonlinearExpressionTreeModIndexes

(

)

Get the number of unique nonlinear expression tree indexes after modifying the expression tree to contain quadratic terms.

Returns:

the number of unique nonlinear expression tree indexes (including quadratic terms).

Definition at line 2714 of file OSInstance.cpp.

int OSInstance::getMatrixNumber

(

)

Get the number of matrices.

Returns:

the number of matrices.

Definition at line 3301 of file OSInstance.cpp.

ENUM_MATRIX_TYPE OSInstance::getMatrixType

(

int

n

)

Get the matrix type.

Returns:

the type of elements contained in the matrix.

Parameters:

n

is the index number associated with the matrix.

Remarks:

only the most general element type is returned. (e.g., if matrix contains both constants and general expressions, matrix type is ENUM_MATRIX_TYPE_general

for possible types see OSParameters.h

ENUM_MATRIX_SYMMETRY OSInstance::getMatrixSymmetry

(

int

n

)

Get the matrix symmetry.

Returns:

the type of symmetry found in the matrix.

Parameters:

n

is the index number associated with the matrix.

Remarks:

for possible symmetry types see OSParameters.h

int OSInstance::getNumberOfColumnsForMatrix

(

int

n

)

Get the number of blocks in the matrix.

Parameters:

n

is the index number associated with the matrix.

Returns:

the number of blocks. Get the number of columns in the matrix.

Parameters:

n

is the index number associated with the matrix.

Returns:

the number of columns.

int OSInstance::getNumberOfRowsForMatrix

(

int

n

)

Get the number of rows in the matrix.

Parameters:

n

is the index number associated with the matrix.

Returns:

the number of rows.

int OSInstance::getNumberOfValuesForMatrix

(

int

n

)

Get the number of (nonzero) values in the matrix.

Parameters:

n

is the index number associated with the matrix.

Returns:

the number of values.

std::string OSInstance::getMatrixName

(

int

n

)

Get the name of the matrix.

Parameters:

n

is the index number associated with the matrix.

Returns:

the matrix name.

bool OSInstance::matrixHasBase

(

int

n

)

Several tools to parse the constructor list of a matrix.

Parameters:

n

is the index number associated with the matrix.

Definition at line 3442 of file OSInstance.cpp.

bool OSInstance::matrixHasElements

(

int

n

)

Definition at line 3450 of file OSInstance.cpp.

bool OSInstance::matrixHasTransformations

(

int

n

)

Definition at line 3458 of file OSInstance.cpp.

bool OSInstance::matrixHasBlocks

(

int

n

)

Definition at line 3466 of file OSInstance.cpp.

int OSInstance::getNumberOfElementConstructors

(

int

n

)

Definition at line 3474 of file OSInstance.cpp.

int OSInstance::getNumberOfTransformationConstructors

(

int

n

)

Definition at line 3482 of file OSInstance.cpp.

int OSInstance::getNumberOfBlocksConstructors

(

int

n

)

Definition at line 3490 of file OSInstance.cpp.

OSMatrix* OSInstance::getMatrix

(

int

n

)

Get the list of constructors of the matrix.

Parameters:

n

is the index number associated with the matrix.

Returns:

the matrix constructors.

GeneralSparseMatrix * OSInstance::getMatrixCoefficientsInColumnMajor

(

int

n

)

Get the (nonzero) elements of the matrix in column major form.

Parameters:

n

is the index number associated with the matrix.

Returns:

the (nonzero) matrix elements.

Definition at line 3499 of file OSInstance.cpp.

GeneralSparseMatrix * OSInstance::getMatrixCoefficientsInRowMajor

(

int

n

)

Get the (nonzero) elements of the matrix in row major form.

Parameters:

n

is the index number associated with the matrix.

Returns:

the (nonzero) matrix elements.

Definition at line 3517 of file OSInstance.cpp.

GeneralSparseMatrix* OSInstance::getMatrixBlockInColumnMajorForm	(	int	n,
		int	columnIdx,
		int	rowIdx
	)

Get the (nonzero) elements of the matrix in symmetric block form.

Parameters:

n

is the index number associated with the matrix.

Returns:

the (nonzero) matrix elements. Get a block of the matrix (in symmetric column major form).

Parameters:

	n	is the index number associated with the matrix.
	columnIdx	is the column index of the block's location
	rowIdx	is the row index of the block's location

Returns:

the (nonzero) matrix elements on column major form.

Remarks:

if the block in this location is empty, return NULL.

int OSInstance::getNumberOfMatrixVariables

(

)

Get the number of matrix variables.

Returns:

the number of matrix variables

Definition at line 3536 of file OSInstance.cpp.

int OSInstance::getNumberOfMatrixObjectives

(

)

Get the number of matrix objectives.

Returns:

the number of matrix objectives

Definition at line 3551 of file OSInstance.cpp.

int OSInstance::getNumberOfMatrixConstraints

(

)

Get the number of matrix constraints.

Returns:

the number of matrix constraints

Definition at line 3566 of file OSInstance.cpp.

int OSInstance::getNumberOfMatrixExpressions

(

)

Get the number of matrix-valued expressions.

Returns:

the number of matrix-valued variables

Definition at line 3581 of file OSInstance.cpp.

MatrixExpression** OSInstance::getMatrixExpressions

(

)

Get the pointers to the roots of all matrix expression trees.

Returns:

an array of pointers to MatrixExpression objects

MatrixExpressionTree* OSInstance::getMatrixExpressionTree

(

int

rowIdx

)

Get the matrix expression tree for a given row index.

Returns:

a matrix expression tree

std::vector<ExprNode*> OSInstance::getMatrixExpressionTreeInPostfix

(

int

rowIdx

)

Get the postfix tokens for a given row index.

Returns:

a vector of pointers to OSnLNodes in postfix, if rowIdx does not index a row with a nonlinear term throw an exception

std::vector<ExprNode*> OSInstance::getMatrixExpressionTreeModInPostfix

(

int

rowIdx

)

Get the postfix tokens for a given row index for the modified Expression Tree (quadratic terms added).

Returns:

a vector of pointers to OSnLNodes in postfix, if rowIdx does not index a row with a nonlinear term throw an exception

std::vector<ExprNode*> OSInstance::getMatrixExpressionTreeInPrefix

(

int

rowIdx

)

Get the prefix tokens for a given row index.

Returns:

a vector of pointers to OSnLNodes in prefix, if rowIdx does not index a row with a nonlinear term throw an exception

std::string OSInstance::getMatrixExpressionTreeInInfix

(

int

rowIdx

)

Get the infix representation for a given row (or objective function) index.

Parameters:

rowIdx

is the index of the row we want to express in infix.

Returns:

a string representation of the tree, if rowIdx does not index a row with a nonlinear term throw an exception

std::map<int, MatrixExpressionTree* > OSInstance::getAllMatrixExpressionTrees

(

)

Returns:

a map: the key is the row index and the value is the corresponding expression tree

std::map<int, MatrixExpressionTree* > OSInstance::getAllMatrixExpressionTreesMod

(

)

Returns:

a map: the key is the row index and the value is the corresponding expression tree

int* OSInstance::getMatrixExpressionTreeIndexes

(

)

Get all the matrix expression tree indexes, i.e.

indexes of matrix objectives or matrix constraints that contain matrix expressions.

Returns:

a pointer to an integer array of matrix expression tree indexes.

int OSInstance::getNumberOfMatrixExpressionTreeIndexes

(

)

Get the number of unique matrix expression tree indexes.

Returns:

the number of unique matrix expression tree indexes.

std::string OSInstance::getTimeDomainFormat

(

)

Get the format of the time domain ("stages"/"interval").

Returns:

the format of the time domain.

Definition at line 4197 of file OSInstance.cpp.

int OSInstance::getTimeDomainStageNumber

(

)

Get the number of stages that make up the time domain.

Returns:

the number of time stages.

Definition at line 4208 of file OSInstance.cpp.

std::string * OSInstance::getTimeDomainStageNames

(

)

Get the names of the stages (NULL or empty string ("") if a stage has not been given a name.

Returns:

the names of time stages.

Definition at line 4226 of file OSInstance.cpp.

int * OSInstance::getTimeDomainStageNumberOfVariables

(

)

Get the number of variables contained in each time stage.

Returns:

a vector of size numberOfStages.

Definition at line 4245 of file OSInstance.cpp.

int * OSInstance::getTimeDomainStageNumberOfConstraints

(

)

Get the number of constraints contained in each time stage.

Returns:

a vector of size numberOfStages.

Definition at line 4263 of file OSInstance.cpp.

int * OSInstance::getTimeDomainStageNumberOfObjectives

(

)

Get the number of objectives contained in each time stage.

Returns:

a vector of size numberOfStages.

Definition at line 4281 of file OSInstance.cpp.

int ** OSInstance::getTimeDomainStageVarList

(

)

Get the list of variables in each stage.

Returns:

one array of integers for each stage.

Definition at line 4299 of file OSInstance.cpp.

int ** OSInstance::getTimeDomainStageConList

(

)

Get the list of constraints in each stage.

Returns:

one array of integers for each stage.

Definition at line 4337 of file OSInstance.cpp.

int ** OSInstance::getTimeDomainStageObjList

(

)

Get the list of objectives in each stage.

Returns:

one array of integers for each stage.

Definition at line 4375 of file OSInstance.cpp.

double OSInstance::getTimeDomainIntervalStart

(

)

Get the start for the time domain interval.

Returns:

start end of the time interval.

Definition at line 4411 of file OSInstance.cpp.

double OSInstance::getTimeDomainIntervalHorizon

(

)

Get the horizon for the time domain interval.

Returns:

the end of the time interval.

Definition at line 4422 of file OSInstance.cpp.

bool OSInstance::setInstanceName

(

std::string

name

)

set the instance name.

Parameters:

name

holds the instance name.

Returns:

whether the instance name was set successfully.

bool OSInstance::setInstanceSource

(

std::string

source

)

set the instance source.

Parameters:

source

holds the instance source.

Returns:

whether the instance source was set successfully.

bool OSInstance::setInstanceDescription

(

std::string

description

)

set the instance description.

Parameters:

description

holds the instance description.

Returns:

whether the instance description was set successfully.

bool OSInstance::setInstanceCreator

(

std::string

fileCreator

)

set the instance creator.

Parameters:

fileCreator

holds the instance creator.

Returns:

whether the instance creator was set successfully.

bool OSInstance::setInstanceLicence

(

std::string

licence

)

set the instance licence.

Parameters:

licence

holds the instance licence.

Returns:

whether the instance licence was set successfully.

bool OSInstance::setVariableNumber

(

int

number

)

set the number of variables.

Parameters:

number

holds the number of variables.

Returns:

whether the number was set successfully.

Definition at line 4469 of file OSInstance.cpp.

bool OSInstance::addVariable	(	int	index,
		std::string	name,
		double	lowerBound,
		double	upperBound,
		char	type
	)

add a variable.

In order to use the add method, the setVariableNumber must first be called so that the number of variables is known ahead of time to allocate appropriate memory. If a variable with the given variable index already exists, the old variable will be replaced.

Parameters:

	index	holds the variable index. It is required.
	name	holds the variable name; use null or empty std::string ("") if no variable name.
	lowerBound	holds the variable lower bound; use -OSDBL_MAX if no lower bound.
	upperBound	holds the variable upper bound; use OSDBL_MAX if no upper bound.
	type	holds the variable type character: C for Continuous, B for Binary, I for Integer, S for String, D for semi-continuous, J for semi-integer (i.e., either 0 or integer >=n).

Returns:

whether the variable was added successfully.

bool OSInstance::setVariables	(	int	number,
		std::string *	names,
		double *	lowerBounds,
		double *	upperBounds,
		char *	types
	)

set all the variable related elements.

All the previous variable-related elements will be deleted.

Parameters:

	number	holds the number of variables. It is required.
	names	holds a std::string array of variable names; use null if no variable names.
	lowerBounds	holds a double array of variable lower bounds; use null if all lower bounds are 0; use -OSDBL_MAX if no lower bound for a specific variable in the array.
	upperBounds	holds a double array of variable upper bounds; use null if no upper bounds; use OSDBL_MAX if no upper bound for a specific variable in the array.
	types	holds a char array of variable types; use null if all variables are continuous; for a specfic variable in the array use C for Continuous, B for Binary, I for Integer, S for String, D for semi-continuous, J for semi-integer (i.e., either 0 or integer >=n).
	inits	holds a double array of varible initial values; use null if no initial values. -- deprecated
	initsString	holds a std::string array of varible initial values; use null if no initial std::string values. -- deprecated

Returns:

whether the variables were set successfully.

bool OSInstance::setObjectiveNumber

(

int

number

)

set the number of objectives.

Parameters:

number

holds the number of objectives.

Returns:

whether the number of objectives was set successfully.

Definition at line 4558 of file OSInstance.cpp.

bool OSInstance::addObjective	(	int	index,
		std::string	name,
		std::string	maxOrMin,
		double	constant,
		double	weight,
		SparseVector *	objectiveCoefficients
	)

add an objective.

In order to use the add method, the setObjectiveNumber must first be called so that the objective number is known ahead of time to allocate appropriate memory. If a objective with the given objective index already exists, the old objective will be replaced. Objective index will start from -1, -2, -3, ... down, with -1 corresponding to the first objective.

Parameters:

	index	holds the objective index. Remember the first objective index is -1, second -2, ...
	name	holds the objective name; use null or empty std::string ("") if no objective name.
	maxOrMin	holds the objective sense or direction; it can only take two values: "max" or "min".
	constant	holds the objective constant; use 0.0 if no objective constant.
	weight	holds the objective weight; use 1.0 if no objective weight.
	objectiveCoefficients	holds the objective coefficients (null if no objective coefficients) in a sparse representation that holds two arrays: index array and a value array.

Returns:

whether the objective was added successfully.

bool OSInstance::setObjectives	(	int	number,
		std::string *	names,
		std::string *	maxOrMins,
		double *	constants,
		double *	weights,
		SparseVector **	objectitiveCoefficients
	)

set all the objectives related elements.

All the previous objective-related elements will be deleted.

Parameters:

	number	holds the number of objectives. It is required.
	names	holds a std::string array of objective names; use null if no objective names.
	maxOrMins	holds a std::string array of objective objective senses or directions: "max" or "min"; use null if all objectives are "min".
	constants	holds a double array of objective constants; use null if all objective constants are 0.0.
	weights	holds a double array of objective weights; use null if all objective weights are 1.0.
	objectiveCoefficients	holds an array of objective coefficients, (null if no objective has any coefficients) For each objective, the coefficients are stored in a sparse representation that holds two arrays: index array and a value array. If for a specific objective, there are no objective coefficients, use null for the corresponding array member.

Returns:

whether the objectives were set successfully.

bool OSInstance::setConstraintNumber

(

int

number

)

set the number of constraints.

Parameters:

number

holds the number of constraints.

Returns:

whether the number of constraints was set successfully.

Definition at line 4672 of file OSInstance.cpp.

bool OSInstance::addConstraint	(	int	index,
		std::string	name,
		double	lowerBound,
		double	upperBound,
		double	constant
	)

add a constraint.

In order to use the add method, the setConstraintNumber must first be called so that the constraint number is known ahead of time to allocate appropriate memory. If a constraint with the given constraint index already exists, the old constraint will be replaced.

Parameters:

	index	holds the constraint index. It is required.
	name	holds the constraint name; use null or empty std::string ("") if no constraint name.
	lowerBound	holds the constraint lower bound; use -OSDBL_MAX if no lower bound.
	upperBound	holds the constraint upper bound; use OSDBL_MAX if no upper bound.

Returns:

whether the constraint was added successfully.

bool OSInstance::setConstraints	(	int	number,
		std::string *	names,
		double *	lowerBounds,
		double *	upperBounds,
		double *	constants
	)

set all the constraint related elements.

All the previous constraint-related elements will be deleted.

Parameters:

	number	holds the number of constraints. It is required.
	names	holds a std::string array of constraint names; use null if no constraint names.
	lowerBounds	holds a double array of constraint lower bounds; use null if no lower bounds; use -OSDBL_MAX if no lower bound for a specific constraint in the array.
	upperBounds	holds a double array of constraint upper bounds; use null if no upper bounds; use OSDBL_MAX if no upper bound for a specific constraint in the array.

Returns:

whether the constraints were set successfully.

bool OSInstance::setLinearConstraintCoefficients	(	int	numberOfValues,
		bool	isColumnMajor,
		double *	values,
		int	valuesBegin,
		int	valuesEnd,
		int *	indexes,
		int	indexesBegin,
		int	indexesEnd,
		int *	starts,
		int	startsBegin,
		int	startsEnd
	)

set linear constraint coefficients

Parameters:

	numberOfValues	holds the number of specified coefficient values (usually nonzero) in the coefficient matrix.
	isColumnMajor	holds whether the coefficient matrix is stored in column major (true) or row major (false).
	values	holds a double array coefficient values in the matrix.
	valuesBegin	holds the begin index of the values array to copy from (usually 0).
	valuesEnd	holds the end index of the values array to copy till (usually values.length - 1).
	indexes	holds an integer array column/row indexes for each value in the values array.
	indexesBegin	holds the begin index of the indexes array to copy from (usually 0).
	indexesEnd	holds the end index of the indexes array to copy till (usually indexes.length - 1).
	starts	holds an integer array start indexes in the matrix; the first value of starts should always be 0.
	startsBegin	holds the begin index of the starts array to copy from (usually 0).
	startsEnd	holds the end index of the starts array to copy till (usually starts.length - 1).

Returns:

whether the linear constraint coefficients were set successfully.

Definition at line 4755 of file OSInstance.cpp.

bool OSInstance::copyLinearConstraintCoefficients	(	int	numberOfValues,
		bool	isColumnMajor,
		double *	values,
		int	valuesBegin,
		int	valuesEnd,
		int *	indexes,
		int	indexesBegin,
		int	indexesEnd,
		int *	starts,
		int	startsBegin,
		int	startsEnd
	)

copy linear constraint coefficients: perform a deep copy of the sparse matrix

Parameters:

	numberOfValues	holds the number of specified coefficient values (usually nonzero) in the coefficient matrix.
	isColumnMajor	holds whether the coefficient matrix is stored in column major (true) or row major (false).
	values	holds a double array coefficient values in the matrix.
	valuesBegin	holds the begin index of the values array to copy from (usually 0).
	valuesEnd	holds the end index of the values array to copy till (usually values.length - 1).
	indexes	holds an integer array column/row indexes for each value in the values array.
	indexesBegin	holds the begin index of the indexes array to copy from (usually 0).
	indexesEnd	holds the end index of the indexes array to copy till (usually indexes.length - 1).
	starts	holds an integer array start indexes in the matrix; the first value of starts should always be 0.
	startsBegin	holds the begin index of the starts array to copy from (usually 0).
	startsEnd	holds the end index of the starts array to copy till (usually starts.length - 1).

Returns:

whether the linear constraint coefficients were copied successfully.

Definition at line 4820 of file OSInstance.cpp.

bool OSInstance::setNumberOfQuadraticTerms

(

int

nq

)

set the number of quadratic terms

Parameters:

nq

holds the number of quadratic terms.

Returns:

whether the number of quadratic terms was set successfully.

Definition at line 4907 of file OSInstance.cpp.

bool OSInstance::setQuadraticCoefficients	(	int	number,
		int *	rowIndexes,
		int *	varOneIndexes,
		int *	varTwoIndexes,
		double *	coefficients,
		int	begin,
		int	end
	)

set quadratic coefficients into the QuadraticCoefficients->qTerm data structure

Parameters:

	number	holds the number of quadratic terms.
	rowIndexes	holds an integer array of row indexes of all the quadratic terms. A negative integer corresponds to an objective row, e.g. -1 for 1st objective and -2 for 2nd.
	varOneIndexes	holds an integer array of the first variable indexes of all the quadratic terms.
	varTwoIndexes	holds an integer array of the second variable indexes of all the quadratic terms.
	coefficients	holds an array of double containing all the quadratic term coefficients.
	begin	holds the begin index of all the arrays to copy from (usually = 0).
	end	holds the end index of all the arrays to copy till (usually = array length -1).

Returns:

whether the quadratic terms were set successfully.

Definition at line 4920 of file OSInstance.cpp.

bool OSInstance::setQuadraticTermsInNonlinearExpressions	(	int	number,
		int *	rowIndexes,
		int *	varOneIndexes,
		int *	varTwoIndexes,
		double *	coefficients
	)

set quadratic terms in nonlinearExpressions

Parameters:

	number	holds the number of quadratic terms.
	rowIndexes	holds an integer array of row indexes of all the quadratic terms. A negative integer corresponds to an objective row, e.g. -1 for 1st objective and -2 for 2nd.
	varOneIndexes	holds an integer array of the first variable indexes of all the quadratic terms.
	varTwoIndexes	holds an integer array of the second variable indexes of all the quadratic terms.
	coefficients	holds a double array all the quadratic term coefficients.

Returns:

whether the quadratic terms were set successfully.

Definition at line 4958 of file OSInstance.cpp.

bool OSInstance::setNonlinearExpressions	(	int	nexpr,
		Nl **	root
	)

set nonlinear expressions

Parameters:

	nexpr	holds the number of nonlinear expressions.
	root	holds a pointer array to the root nodes of all the nonlinear expressions.

Returns:

whether the nonlinear expressions were set successfully.

Definition at line 4996 of file OSInstance.cpp.

bool OSInstance::setMatrixNumber

(

int

number

)

set the number of matrices

Parameters:

number

holds the number of matrices

Returns:

whether the number of matrices was set successfully.

Definition at line 5240 of file OSInstance.cpp.

bool OSInstance::addMatrix	(	int	index,
		std::string	name,
		int	numberOfRows,
		int	numberOfColumns,
		ENUM_MATRIX_SYMMETRY	symmetry,
		ENUM_MATRIX_TYPE	matrixType,
		unsigned int	inumberOfChildren,
		MatrixNode **	m_mChildren
	)

add a matrix.

In order to use the add method, the setMatrixNumber must first be called so that the number of matrices is known ahead of time to allocate appropriate memory. If a matrix with the given matrix index already exists, the old matrix will be replaced.

Parameters:

	index	holds the matrix index. It is required.
	name	holds the matrix name; use null or empty std::string ("") if no matrix name.
	numberOfRows	holds the number of rows. It is required. Use 1 for column vectors.
	numberOfColumns	holds the number of columns. It is required. Use 1 for row vectors.
	symmetry	holds the type of symmetry used in the definition of the matrix. For more information see the enumeration ENUM_MATRIX_SYMMETRY in OSGeneral.h. If no symmetry, use ENUM_MATRIX_SYMMETRY_none.
	matrixType	tracks the type of elements contained in this matrix. For more information see the enumeration ENUM_MATRIX_TYPE in OSGeneral.h. If unsure, use ENUM_MATRIX_TYPE_unknown.
	inumberOfChildren	is the number of MatrixNode child elements, i.e., the number of matrix constructors in the m_mChildren array.
	m_mChildren	is the array of matrix constructors used in the definition of this matrix.

Returns:

whether the matrix was added successfully.

Definition at line 5255 of file OSInstance.cpp.

bool OSInstance::setConeNumber

(

int

number

)

set the number of cones

Parameters:

number

holds the number of cones

Returns:

whether the number of cones was set successfully.

Definition at line 5267 of file OSInstance.cpp.

bool OSInstance::addCone	(	int	index,
		int	numberOfRows,
		int	numberOfColumns,
		ENUM_CONE_TYPE	coneType,
		std::string	name,
		int	numberOfOtherIndexes = 0,
		int *	otherIndexes = NULL
	)

add a cone.

In order to use the add method, the setConeNumber must first be called so that the number of cones is known ahead of time to allocate appropriate memory. If a cone with the given cone index already exists, the old cone will be replaced.

Remarks:

This method has different signatures to cater for different types of cones. This signature is used for cones that require basic information only.

Parameters:

	index	holds the cone index. It is required.
	numberOfRows	holds the number of rows. It is required.
	numberOfColumns	holds the number of columns. It is required.
	coneType	holds the cone type. For more information consult the enumeration ENUM_CONE_TYPE further up in this file. This argument is required and must be one of ENUM_CONE_TYPE_nonnegative, ENUM_CONE_TYPE_nonpositive, ENUM_CONE_TYPE_copositiveMatrices, ENUM_CONE_TYPE_completelyPositiveMatrices.
	name	holds the cone name; use null or empty std::string ("") if no cone name.
	numberOfOtherIndexes	holds the number of other indexes if the cone contains higher-dimensional tensors. This argument is optional and can be omitted. It defaults to 0.
	otherIndexes	holds the array of other indexes if the cone contains higher-dimensional tensors. This argument is optional and can be omitted. It defaults to null.

Returns:

whether the cone was added successfully.

Definition at line 5280 of file OSInstance.cpp.

bool OSInstance::addCone	(	int	index,
		int	numberOfRows,
		int	numberOfColumns,
		ENUM_CONE_TYPE	coneType,
		std::string	name,
		int	numberOfComponents,
		int *	components,
		int	numberOfOtherIndexes = 0,
		int *	otherIndexes = NULL
	)

add a cone.

In order to use the add method, the setConeNumber must first be called so that the number of cones is known ahead of time to allocate appropriate memory. If a cone with the given cone index already exists, the old cone will be replaced.

Remarks:

This method has different signatures to cater for different types of cones. This signature is used for product and intersection cones.

Parameters:

	index	holds the cone index. It is required.
	numberOfRows	holds the number of rows. It is required.
	numberOfColumns	holds the number of columns. It is required.
	coneType	holds the cone type. For more information consult the enumeration ENUM_CONE_TYPE further up in this file. This argument is required and must be one of ENUM_CONE_TYPE_product, ENUM_CONE_TYPE_intersection.
	name	holds the cone name; use null or empty std::string ("") if no cone name.
	numberOfComponents	holds the number of components of this cone.
	components	holds the indexes of the components of this cone.
	numberOfOtherIndexes	holds the number of other indexes if the cone contains higher-dimensional tensors. This argument is optional and can be omitted. It defaults to 0.
	otherIndexes	holds the array of other indexes if the cone contains higher-dimensional tensors. This argument is optional and can be omitted. It defaults to null.

Returns:

whether the cone was added successfully.

Definition at line 5333 of file OSInstance.cpp.

bool OSInstance::addCone	(	int	index,
		int	numberOfRows,
		int	numberOfColumns,
		ENUM_CONE_TYPE	coneType,
		std::string	name,
		int	referenceIdx,
		int	numberOfOtherIndexes = 0,
		int *	otherIndexes = NULL
	)

add a cone.

In order to use the add method, the setConeNumber must first be called so that the number of cones is known ahead of time to allocate appropriate memory. If a cone with the given cone index already exists, the old cone will be replaced.

Remarks:

This method has different signatures to cater for different types of cones. This signature is used for positive or negative cones that reference another cone or matrix.

Parameters:

	index	holds the cone index. It is required.
	numberOfRows	holds the number of rows. It is required.
	numberOfColumns	holds the number of columns. It is required.
	coneType	holds the cone type. For more information consult the enumeration ENUM_CONE_TYPE further up in this file. This argument is required and must be one of ENUM_CONE_TYPE_dual, ENUM_CONE_TYPE_polar, ENUM_CONE_TYPE_polyhedral.
	name	holds the cone name; use null or empty std::string ("") if no cone name.
	referenceIdx	holds the index of a cone or matrix used in the definition of this cone.
	numberOfOtherIndexes	holds the number of other indexes if the cone contains higher-dimensional tensors. This argument is optional and can be omitted. It defaults to 0.
	otherIndexes	holds the array of other indexes if the cone contains higher-dimensional tensors. This argument is optional and can be omitted. It defaults to null.

Returns:

whether the cone was added successfully.

Definition at line 5375 of file OSInstance.cpp.

bool OSInstance::addCone	(	int	index,
		int	numberOfRows,
		int	numberOfColumns,
		ENUM_CONE_TYPE	coneType,
		std::string	name,
		std::string	semidefiniteness,
		int	numberOfOtherIndexes = 0,
		int *	otherIndexes = NULL
	)

add a cone.

In order to use the add method, the setConeNumber must first be called so that the number of cones is known ahead of time to allocate appropriate memory. If a cone with the given cone index already exists, the old cone will be replaced.

Remarks:

This method has different signatures to cater for different types of cones. This signature is used for positive or negative semidefinite cones.

Parameters:

	index	holds the cone index. It is required.
	numberOfRows	holds the number of rows. It is required.
	numberOfColumns	holds the number of columns. It is required.
	coneType	holds the cone type. For more information consult the enumeration ENUM_CONE_TYPE further up in this file. This argument is required and must be ENUM_CONE_TYPE_semidefinite.
	name	holds the cone name; use null or empty std::string ("") if no cone name.
	semidefiniteness	distinguishes positive and negative semidefinite cones. It must be either "positive" or "negative".
	numberOfOtherIndexes	holds the number of other indexes if the cone contains higher-dimensional tensors. This argument is optional and can be omitted. It defaults to 0.
	otherIndexes	holds the array of other indexes if the cone contains higher-dimensional tensors. This argument is optional and can be omitted. It defaults to null.

Returns:

whether the cone was added successfully.

Definition at line 5424 of file OSInstance.cpp.

bool OSInstance::addCone	(	int	index,
		int	numberOfRows,
		int	numberOfColumns,
		ENUM_CONE_TYPE	coneType,
		std::string	name,
		int	distortionMatrixIdx,
		double	normFactor,
		int	axisDirection,
		int	numberOfOtherIndexes = 0,
		int *	otherIndexes = NULL
	)

add a cone.

In order to use the add method, the setConeNumber must first be called so that the number of cones is known ahead of time to allocate appropriate memory. If a cone with the given cone index already exists, the old cone will be replaced.

Remarks:

This method has different signatures to cater for different types of cones. This signature is used for quadratic cones.

Parameters:

	index	holds the cone index. It is required.
	numberOfRows	holds the number of rows. It is required.
	numberOfColumns	holds the number of columns. It is required.
	coneType	holds the cone type. For more information consult the enumeration ENUM_CONE_TYPE further up in this file. This argument is required and must be ENUM_CONE_TYPE_quadratic.
	name	holds the cone name; use null or empty std::string ("") if no cone name.
	distortionMatrixIdx	holds the index of a distortion matrix. Use -1 if there is none.
	normFactor	holds a scale factor for the norm. Use 1 if there is none.
	axisDirection	holds the index of the axis direction. The most usual value is 0.
	numberOfOtherIndexes	holds the number of other indexes if the cone contains higher-dimensional tensors. This argument is optional and can be omitted. It defaults to 0.
	otherIndexes	holds the array of other indexes if the cone contains higher-dimensional tensors. This argument is optional and can be omitted. It defaults to null.

Returns:

whether the cone was added successfully.

Definition at line 5447 of file OSInstance.cpp.

bool OSInstance::addCone	(	int	index,
		int	numberOfRows,
		int	numberOfColumns,
		ENUM_CONE_TYPE	coneType,
		std::string	name,
		int	distortionMatrixIdx,
		double	normFactor,
		int	firstAxisDirection,
		int	secondAxisDirection,
		int	numberOfOtherIndexes = 0,
		int *	otherIndexes = NULL
	)

add a cone.

In order to use the add method, the setConeNumber must first be called so that the number of cones is known ahead of time to allocate appropriate memory. If a cone with the given cone index already exists, the old cone will be replaced.

Remarks:

This method has different signatures to cater for different types of cones. This signature is used for rotated quadratic cones.

Parameters:

	index	holds the cone index. It is required.
	numberOfRows	holds the number of rows. It is required.
	numberOfColumns	holds the number of columns. It is required.
	coneType	holds the cone type. For more information consult the enumeration ENUM_CONE_TYPE further up in this file. This argument is required and must be ENUM_CONE_TYPE_rotatedQuadratic.
	name	holds the cone name; use null or empty std::string ("") if no cone name.
	distortionMatrixIdx	holds the index of a distortion matrix. Use -1 if there is none.
	normFactor	holds a scale factor for the norm. Use 1 if there is none.
	firstAxisDirection	holds the index of the first axis direction. The most usual value is 0.
	secondAxisDirection	holds the index of the second axis direction. The most usual value is 1.
	numberOfOtherIndexes	holds the number of other indexes if the cone contains higher-dimensional tensors. This argument is optional and can be omitted. It defaults to 0.
	otherIndexes	holds the array of other indexes if the cone contains higher-dimensional tensors. This argument is optional and can be omitted. It defaults to null.

Returns:

whether the cone was added successfully.

Definition at line 5473 of file OSInstance.cpp.

bool OSInstance::addCone	(	int	index,
		int	numberOfRows,
		int	numberOfColumns,
		ENUM_CONE_TYPE	coneType,
		std::string	name,
		int	distortionMatrixIdx,
		double	normFactor,
		int	axisDirection,
		double	pNorm,
		int	numberOfOtherIndexes = 0,
		int *	otherIndexes = NULL
	)

add a cone.

In order to use the add method, the setConeNumber must first be called so that the number of cones is known ahead of time to allocate appropriate memory. If a cone with the given cone index already exists, the old cone will be replaced.

Remarks:

This method has different signatures to cater for different types of cones. This signature is used for normed cones.

Parameters:

	index	holds the cone index. It is required.
	numberOfRows	holds the number of rows. It is required.
	numberOfColumns	holds the number of columns. It is required.
	coneType	holds the cone type. For more information consult the enumeration ENUM_CONE_TYPE further up in this file. This argument is required and must be ENUM_CONE_TYPE_normed.
	name	holds the cone name; use null or empty std::string ("") if no cone name.
	distortionMatrixIdx	holds the index of a distortion matrix. Use -1 if there is none.
	normFactor	holds a scale factor for the norm. Use 1 if there is none.
	pNorm	holds the norm descriptor. It must be greater than or equal to 1.
	numberOfOtherIndexes	holds the number of other indexes if the cone contains higher-dimensional tensors. This argument is optional and can be omitted. It defaults to 0.
	otherIndexes	holds the array of other indexes if the cone contains higher-dimensional tensors. This argument is optional and can be omitted. It defaults to null.

Returns:

whether the cone was added successfully.

Definition at line 5504 of file OSInstance.cpp.

bool OSInstance::addCone	(	int	index,
		int	numberOfRows,
		int	numberOfColumns,
		ENUM_CONE_TYPE	coneType,
		std::string	name,
		int	maxDegree,
		int	numberOfUB,
		double *	ub,
		int	numberOfLB,
		double *	lb,
		int	numberOfOtherIndexes = 0,
		int *	otherIndexes = NULL
	)

add a cone.

In order to use the add method, the setConeNumber must first be called so that the number of cones is known ahead of time to allocate appropriate memory. If a cone with the given cone index already exists, the old cone will be replaced.

Remarks:

This method has different signatures to cater for different types of cones. This signature is used for cones of nonnegative polynomials and similar cones.

Parameters:

	index	holds the cone index. It is required.
	numberOfRows	holds the number of rows. It is required.
	numberOfColumns	holds the number of columns. It is required.
	coneType	holds the cone type. For more information consult the enumeration ENUM_CONE_TYPE further up in this file. This argument is required and must be ENUM_CONE_TYPE_nonnegativePolynomials. ENUM_CONE_TYPE_sumOfSquaresPolynomials. ENUM_CONE_TYPE_moment.
	name	holds the cone name; use null or empty std::string ("") if no cone name.
	maxDegree	holds the maximum degree of the polynomials. Use 1, 2, 3, ..., INF.
	numberOfUB	holds the number of (box-type) upper bound constraints. Use 0 if there are none.
	ub	holds the upper bound values. Use null if there are no upper bounds.
	numberOfLB	holds the number of (box-type) lower bound constraints. Use 0 if there are none.
	lb	holds the lower bound values. Use null if there are no lower bounds.
	numberOfOtherIndexes	holds the number of other indexes if the cone contains higher-dimensional tensors. This argument is optional and can be omitted. It defaults to 0.
	otherIndexes	holds the array of other indexes if the cone contains higher-dimensional tensors. This argument is optional and can be omitted. It defaults to null.

Returns:

whether the cone was added successfully.

Definition at line 5533 of file OSInstance.cpp.

std::string OSInstance::printModel

(

)

Print the infix representation of the problem.

Returns:

a string with the infix representation

Definition at line 5585 of file OSInstance.cpp.

std::string OSInstance::printModel

(

int

rowIdx

)

Print the infix representation of the row (which could be an an objective function row) indexed by rowIdx.

Parameters:

rowIdx

is the index of the row we want to express in infix.

Returns:

a string with the infix representation

Definition at line 5652 of file OSInstance.cpp.

bool OSInstance::initializeNonLinearStructures

(

)

Initialize the data structures for the nonlinear API.

Returns:

true if we have initialized the nonlinear data strucutres.

Definition at line 5022 of file OSInstance.cpp.

double OSInstance::calculateFunctionValue	(	int	idx,
		double *	x,
		bool	new_x
	)

Calculate the function value for function (constraint or objective) indexed by idx.

Parameters:

	idx	is the index on the constraint (0, 1, 2, 3, ...) or objective function (-1, -2, -3, ...).
	x	is a pointer (double array) to the current variable values
	new_x	is false if any evaluation method was previously called for the current x has been evaluated for the current iterate x use a value of false if not sure

Returns:

the function value as a double.

Definition at line 5769 of file OSInstance.cpp.

double * OSInstance::calculateAllConstraintFunctionValues	(	double *	x,
		double *	objLambda,
		double *	conLambda,
		bool	new_x,
		int	highestOrder
	)

Calculate all of the constraint function values.

Parameters:

	x	is a pointer (double array) to the current variable values
	objLambda	is the Lagrange multiplier on the objective function
	conLambda	is pointer (double array) of Lagrange multipliers on the constratins
	new_x	is false if any evaluation method was previously called for the current x for the current iterate
	highestOrder	is the highest order of the derivative being calculated

Returns:

a double array of constraint function values -- the size of the array is equal to getConstraintNumber().

Definition at line 5834 of file OSInstance.cpp.

double * OSInstance::calculateAllConstraintFunctionValues	(	double *	x,
		bool	new_x
	)

Calculate all of the constraint function values, we are overloading this function and this version of the method will not use any AD and will evaluate function values from the OS Expression Tree.

Parameters:

	x	is a pointer (double array) to the current variable values
	new_x	is false if any evaluation method was previously called for the current iterate

Returns:

a double array of constraint function values -- the size of the array is equal to getConstraintNumber().

Definition at line 5850 of file OSInstance.cpp.

double * OSInstance::calculateAllObjectiveFunctionValues	(	double *	x,
		double *	objLambda,
		double *	conLambda,
		bool	new_x,
		int	highestOrder
	)

Calculate all of the objective function values.

Parameters:

	x	is a pointer (double array) to the current variable values
	objLambda	is the Lagrange multiplier on the objective function
	conLambda	is pointer (double array) of Lagrange multipliers on the constratins
	new_x	is false if any evaluation method was previously called for the current iterate
	highestOrder	is the highest order of the derivative being calculated

Returns:

a double array of objective function values -- the size of the array is equal to getObjectiveNumber().

Definition at line 5873 of file OSInstance.cpp.

double * OSInstance::calculateAllObjectiveFunctionValues	(	double *	x,
		bool	new_x
	)

Calculate all of the objective function values, we are overloading this function and this version of the method will not use any AD and will evaluate function values from the OS Expression Tree.

Parameters:

	x	is a pointer (double array) to the current variable values
	new_x	is false if any evaluation method was previously called for the current iterate

Returns:

a double array of objective function values -- the size of the array is equal to getObjectiveNumber().

Definition at line 5889 of file OSInstance.cpp.

SparseJacobianMatrix * OSInstance::calculateAllConstraintFunctionGradients	(	double *	x,
		double *	objLambda,
		double *	conLambda,
		bool	new_x,
		int	highestOrder
	)

Calculate the gradient of all constraint functions.

Parameters:

	x	is a pointer (double array) to the current variable values
	objLambda	is the Lagrange multiplier on the objective function
	conLambda	is pointer (double array) of Lagrange multipliers on the constratins
	new_x	is false if any evaluation method was previously called for the current iterate
	highestOrder	is the highest order of the derivative being calculated

Returns:

a pointer a SparseJacobianMatrix.

Definition at line 5912 of file OSInstance.cpp.

SparseVector * OSInstance::calculateConstraintFunctionGradient	(	double *	x,
		double *	objLambda,
		double *	conLambda,
		int	idx,
		bool	new_x,
		int	highestOrder
	)

Calculate the gradient of the constraint function indexed by idx.

Parameters:

	x	is a pointer (double array) to the current variable values
	objLambda	is the Lagrange multiplier on the objective function
	conLambda	is pointer (double array) of Lagrange multipliers on the constratins idx is the index of the constraint function gradient
	new_x	is false if any evaluation method was previously called for the current iterate
	highestOrder	is the highest order of the derivative being calculated

Returns:

a pointer to a sparse vector of doubles.

Definition at line 5931 of file OSInstance.cpp.

SparseVector * OSInstance::calculateConstraintFunctionGradient	(	double *	x,
		int	idx,
		bool	new_x
	)

Calculate the gradient of the constraint function indexed by idx this function is overloaded.

Parameters:

	x	is a pointer (double array) to the current variable values idx is the index of the constraint function gradient
	new_x	is false if any evaluation method was previously called for the current iterate
	highestOrder	is the highest order of the derivative being calculated

Returns:

a pointer to a sparse vector of doubles.

Definition at line 5962 of file OSInstance.cpp.

double ** OSInstance::calculateAllObjectiveFunctionGradients	(	double *	x,
		double *	objLambda,
		double *	conLambda,
		bool	new_x,
		int	highestOrder
	)

Calculate the gradient of all objective functions.

Parameters:

	x	is a pointer (double array) to the current variable values
	objLambda	is the Lagrange multiplier on the objective function
	conLambda	is pointer (double array) of Lagrange multipliers on the constratins
	new_x	is false if any evaluation method was previously called for the current iterate
	highestOrder	is the highest order of the derivative being calculated

Returns:

an array of pointer to dense objective function gradients.

Definition at line 5991 of file OSInstance.cpp.

double * OSInstance::calculateObjectiveFunctionGradient	(	double *	x,
		double *	objLambda,
		double *	conLambda,
		int	objIdx,
		bool	new_x,
		int	highestOrder
	)

Calculate the gradient of the objective function indexed by objIdx.

Parameters:

	x	is a pointer (double array) to the current variable values
	objLambda	is the Lagrange multiplier on the objective function
	conLambda	is pointer (double array) of Lagrange multipliers on the constratins objIdx is the index of the objective function being optimized
	new_x	is false if any evaluation method was previously called for the current iterate
	highestOrder	is the highest order of the derivative being calculated

Returns:

a pointer to a dense vector of doubles.

Definition at line 6017 of file OSInstance.cpp.

double * OSInstance::calculateObjectiveFunctionGradient	(	double *	x,
		int	objIdx,
		bool	new_x
	)

Calculate the gradient of the objective function indexed by objIdx this function is overloaded.

Parameters:

	x	is a pointer (double array) to the current variable values
	objIdx	is the index of the objective function being optimized
	new_x	is false if any evaluation method was previously called for the current iterate

Returns:

a pointer to a dense vector of doubles.

Definition at line 6081 of file OSInstance.cpp.

SparseHessianMatrix * OSInstance::calculateLagrangianHessian	(	double *	x,
		double *	objLambda,
		double *	conLambda,
		bool	new_x,
		int	highestOrder
	)

Calculate the Hessian of the Lagrangian Expression Tree This method will build the CppAD expression tree for only the first iteration Use this method on if the value of x does not affect the operations sequence.

Parameters:

	x	is a pointer (double array) to the current variable values
	objLambda	is the Lagrange multiplier on the objective function
	conLambda	is pointer (double array) of Lagrange multipliers on the constratins
	new_x	is false if any evaluation method was previously called for the current iterate
	highestOrder	is the highest order of the derivative being calculated

Returns:

a pointer a SparseHessianMatrix. Each array member corresponds to one constraint gradient.

Definition at line 6135 of file OSInstance.cpp.

SparseHessianMatrix * OSInstance::calculateHessian	(	double *	x,
		int	idx,
		bool	new_x
	)

Calculate the Hessian of a constraint or objective function.

Parameters:

	x	is a pointer (double array) to the current variable values
	new_x	is false if any evaluation method was previously called for the current iterate idx is the index of the either a constraint or objective function Hessian

Returns:

a pointer a SparseVector. Each array member corresponds to one constraint gradient.

Definition at line 6153 of file OSInstance.cpp.

bool OSInstance::getSparseJacobianFromColumnMajor

(

)

Returns:

true if successful in generating the constraints gradient.

Definition at line 6197 of file OSInstance.cpp.

bool OSInstance::getSparseJacobianFromRowMajor

(

)

Returns:

true if successful in generating the constraints gradient.

Definition at line 6374 of file OSInstance.cpp.

ScalarExpressionTree * OSInstance::getLagrangianExpTree

(

)

Returns:

a pointer to the ExpressionTree for the Lagrangian function of current instance we only take the Lagrangian of the rows with nonlinear terms

Definition at line 6538 of file OSInstance.cpp.

std::map< int, int > OSInstance::getAllNonlinearVariablesIndexMap

(

)

Returns:

a pointer to a map of the indices of all of the variables that appear in the Lagrangian function

Definition at line 6591 of file OSInstance.cpp.

SparseHessianMatrix * OSInstance::getLagrangianHessianSparsityPattern

(

)

Returns:

a pointer to a SparseHessianMatrix with the nonzero structure of the Lagrangian Expression Tree

Definition at line 6637 of file OSInstance.cpp.

bool OSInstance::addQTermsToExressionTree

(

)

Returns:

true if successful in adding the qTerms to the ExpressionTree.

Remarks:

due to the typo in the name of the method, this has been flagged as obsolescent and is being replaced by addQTermsToExpressionTree() -- see below

Definition at line 5102 of file OSInstance.cpp.

bool OSInstance::addQTermsToExpressionTree

(

)

This method adds quadratic terms into the array of expression trees.

There is at most one expression tree per row (see getAllNonlinearExpressionTrees)

Returns:

true if successful in adding the qTerms to the ExpressionTree.

Definition at line 5107 of file OSInstance.cpp.

SparseJacobianMatrix * OSInstance::getJacobianSparsityPattern

(

)

Returns:

pointer to a SparseJacobianMatrix.

Definition at line 5058 of file OSInstance.cpp.

void OSInstance::duplicateExpressionTreesMap

(

)

duplicate the map of expression trees.

Definition at line 6706 of file OSInstance.cpp.

bool OSInstance::createOSADFun

(

std::vector< double >

vdX

)

Create the a CppAD Function object: this is a function where the domain is the set of variables for the problem and the range is the objective function plus constraints.

Parameters:

vdX

is a vector of doubles holding the current primal variable values the size of x should equal instanceData->variables->numberOfVariables

Returns:

if successfully created

Definition at line 7658 of file OSInstance.cpp.

std::vector< double > OSInstance::forwardAD	(	int	p,
		std::vector< double >	vdX
	)

Perform an AD forward sweep.

Parameters:

	p	is the highest order Taylor coefficient
	vdX	is a vector of doubles of the current primal variable values the size of vdX m_iNumberOfNonlinearVariables

Returns:

a double vector equal to the dimension of the range space the result of the forward p sweep

Definition at line 7715 of file OSInstance.cpp.

std::vector< double > OSInstance::reverseAD	(	int	p,
		std::vector< double >	vdlambda
	)

Perform an AD reverse sweep.

Parameters:

	p	is the order of the sweep
	vdlambda	is a vector of doubles of the current dual (lagrange) variable values the size of lambda should equal number of objective functions plus number of constraints

Returns:

a double vector equal to the n*p

Definition at line 7740 of file OSInstance.cpp.

int OSInstance::getADSparsityHessian

(

)

end revised AD code

Call the AD routine to fill in m_vbLagHessNonz and determine the nonzeros.

Returns:

the number of nonzeros in the Hessian

Definition at line 7764 of file OSInstance.cpp.

bool OSInstance::getIterateResults	(	double *	x,
		double *	objLambda,
		double *	conLambda,
		bool	new_x,
		int	highestOrder
	)

end revised AD code

Get the information for each iteration. Get the functions values, Jacobian and Hessian of the Lagrangian

Parameters:

	x	is a pointer of doubles of primal values for the current iteration
	objLambda	is is a pointer of doubles of the current dual (Lagrange) multipliers on the objective functions
	conLambda	is a pointer of doubles of the current dual (Lagrange) multipliers on the constraints
	new_x	is false if any evaluation method was previously called
	highestOrder	is the highest order derivative to be calculated

Returns:

true if successful

Definition at line 6724 of file OSInstance.cpp.

bool OSInstance::getZeroOrderResults	(	double *	x,
		double *	objLambda,
		double *	conLambda
	)

Calculate function values.

Parameters:

	x	is a pointer of doubles of primal values for the current iteration
	objLambda	is is a pointer of doubles of the current dual (Lagrange) multipliers on the objective functions
	conLambda	is a pointer of doubles of the current dual (Lagrange) multipliers on the constraints

Returns:

true if successful

Definition at line 6800 of file OSInstance.cpp.

bool OSInstance::getFirstOrderResults	(	double *	x,
		double *	objLambda,
		double *	conLambda
	)

Calculate first derivatives.

Parameters:

	x	is a pointer of doubles of primal values for the current iteration
	objLambda	is is a pointer of doubles of the current dual (Lagrange) multipliers on the objective functions
	conLambda	is a pointer of doubles of the current dual (Lagrange) multipliers on the constraints

Returns:

true if successful

if the number of columns exceeds the number of rows we will get the Jacobian by row, however, if the number of rows exceeds the number of columns we get the Jacobian by column

Definition at line 6866 of file OSInstance.cpp.

bool OSInstance::getSecondOrderResults	(	double *	x,
		double *	objLambda,
		double *	conLambda
	)

Calculate second derivatives.

Parameters:

	x	is a pointer of doubles of primal values for the current iteration
	objLambda	is is a pointer of doubles of the current dual (Lagrange) multipliers on the objective functions
	conLambda	is a pointer of doubles of the current dual (Lagrange) multipliers on the constraints

Returns:

true if successful

Definition at line 6991 of file OSInstance.cpp.

bool OSInstance::initForAlgDiff

(

)

This should be called by nonlinear solvers using callback functions.

initForAlgDiff will initialize the correct nonlinear structures in preparation for using the algorithmic differentiation routines.

Returns:

true if successful

Definition at line 7105 of file OSInstance.cpp.

bool OSInstance::initObjGradients

(

)

This should be called by initForAlgDiff().

initObjGradients will initialize the objective function gradients to be equal to the coefficients given in the <coef> section of the OSiL instance

Returns:

true if successful

Definition at line 7141 of file OSInstance.cpp.

bool OSInstance::setTimeDomain

(

std::string

format

)

This sets the format of the time domain ("stages"/"interval"/"none").

end revised AD test code

set methods for matrices object set methods for cones object set methods for timeDomain object

Definition at line 7185 of file OSInstance.cpp.

bool OSInstance::setTimeDomainStages	(	int	number,
		std::string *	names
	)

This sets the number (and optionally names) of the time stages.

set time domain stages

Definition at line 7235 of file OSInstance.cpp.

bool OSInstance::setTimeDomainStageVariablesOrdered	(	int	numberOfStages,
		int *	numberOfVariables,
		int *	startIdx
	)

This sets the variables associated with each time domain stage in temporal order.

set time domain stage variables in temporal order

(I.e., for each stage numberOfVariables gives the number of variables accociated with this stage and startIdx gives the first variable in this stage.)

Definition at line 7321 of file OSInstance.cpp.

bool OSInstance::setTimeDomainStageVariablesUnordered	(	int	numberOfStages,
		int *	numberOfVariables,
		int **	varIndex
	)

This sets the variables associated with each time domain stage in srbitrary order.

set time domain stage variables in arbitrary order

(I.e., for each stage numberOfVariables gives the number of variables accociated with this stage and varIndex[i] gives the index of each variable in stage[i].)

Definition at line 7363 of file OSInstance.cpp.

bool OSInstance::setTimeDomainStageConstraintsOrdered	(	int	numberOfStages,
		int *	numberOfConstraints,
		int *	startIdx
	)

This sets the constraints associated with each time domain stage in temporal order.

set time domain stage constraints in temporal order

(I.e., for each stage numberOfConstraints gives the number of constraints accociated with this stage and startIdx gives the first constraint in this stage.)

Definition at line 7429 of file OSInstance.cpp.

bool OSInstance::setTimeDomainStageConstraintsUnordered	(	int	numberOfStages,
		int *	numberOfConstraints,
		int **	conIndex
	)

This sets the constraints associated with each time domain stage in srbitrary order.

set time domain stage constraints in arbitrary order

(I.e., for each stage numberOfConstraints gives the number of constraints accociated with this stage and conIndex[i] gives the index of each constraint in stage[i].)

Definition at line 7471 of file OSInstance.cpp.

bool OSInstance::setTimeDomainStageObjectivesOrdered	(	int	numberOfStages,
		int *	numberOfObjectives,
		int *	startIdx
	)

This sets the objectives associated with each time domain stage in temporal order.

set time domain stage objectives in temporal order

(I.e., for each stage numberOfObjectives gives the number of objectives accociated with this stage and startIdx gives the first objective in this stage.)

Definition at line 7537 of file OSInstance.cpp.

bool OSInstance::setTimeDomainStageObjectivesUnordered	(	int	numberOfStages,
		int *	numberOfObjectives,
		int **	varIndex
	)

This sets the objectives associated with each time domain stage in arbitrary order.

set time domain stage objectives in arbitrary order

(I.e., for each stage numberOfObjectives gives the number of objectives accociated with this stage and objIndex[i] gives the index of each objective in stage[i].)

Definition at line 7580 of file OSInstance.cpp.

bool OSInstance::setTimeDomainInterval	(	double	start,
		double	horizon
	)

This sets the start and end of the time interval.

set time domain interval

Definition at line 7644 of file OSInstance.cpp.

bool OSInstance::processVariables

(

)

[private]

process variables.

Returns:

true if the variables are processed.

Exceptions:

Exception

if the elements in variables are logically inconsistent.

bool OSInstance::processObjectives

(

)

[private]

process objectives.

Returns:

true if the objectives are processed.

Exceptions:

Exception

if the elements in objectives are logically inconsistent.

bool OSInstance::processConstraints

(

)

[private]

process constraints.

Returns:

true if the constraints are processed.

Exceptions:

Exception

if the elements in constraints are logically inconsistent.

bool OSInstance::processLinearConstraintCoefficients

(

)

[private]

process linear constraint coefficients.

Returns:

true if the linear constraint coefficients are processed.

Exceptions:

Exception

if the elements in linear constraint coefficients are logically inconsistent.

std::string OSInstance::getInstanceName

(

)

Get instance name.

Returns:

instance name. Null or empty std::string ("") if there is no instance name.

std::string OSInstance::getInstanceSource

(

)

Get instance source.

Returns:

instance source. Null or empty std::string ("") if there is no instance source.

std::string OSInstance::getInstanceDescription

(

)

Get instance description.

Returns:

instance description. Null or empty std::string ("") if there is no instance description.

int OSInstance::getVariableNumber

(

)

Get variable number.

Returns:

variable number.

std::string* OSInstance::getVariableNames

(

)

Get variable names.

Returns:

a std::string array of variable names, null if no variable names.

Exceptions:

Exception

if the elements in variables are logically inconsistent.

char* OSInstance::getVariableTypes

(

)

Get variable initial values.

Returns:

a double array of variable initial values, null if no initial variable values.

Exceptions:

Exception

if the elements in variables are logically inconsistent. -- now deprecated Get variable initial std::string values.

Returns:

a std::string array of variable initial values, null if no initial variable std::string values.

Exceptions:

Exception

if the elements in variables are logically inconsistent. -- now deprecated Get variable types. C for Continuous B for Binary I for Integer S for String

Returns:

a char array of variable types.

Exceptions:

Exception

if the elements in variables are logically inconsistent.

int OSInstance::getNumberOfIntegerVariables

(

)

getNumberOfIntegerVariables

Returns:

an integer which is the number of I variables.

int OSInstance::getNumberOfBinaryVariables

(

)

getNumberOfBinaryVariables

Returns:

an integer which is the number of B variables.

double* OSInstance::getVariableLowerBounds

(

)

Get variable lower bounds.

Returns:

a double array of variable lower bounds.

Exceptions:

Exception

if the elements in variables are logically inconsistent.

double* OSInstance::getVariableUpperBounds

(

)

Get variable upper bounds.

Returns:

a double array of variable upper bounds.

Exceptions:

Exception

if the elements in variables are logically inconsistent.

int OSInstance::getObjectiveNumber

(

)

Get objective number.

Returns:

objective number.

std::string* OSInstance::getObjectiveNames

(

)

Get objective names.

Returns:

a std::string array of objective names. Null if no objective names.

Exceptions:

Exception

if the elements in objectives are logically inconsistent.

std::string* OSInstance::getObjectiveMaxOrMins

(

)

Get objective maxOrMins.

One maxOrMin for each objective.

Returns:

a std::string array of objective maxOrMins ("max" or "min"), null if no objectives.

Exceptions:

Exception

if the elements in objectives are logically inconsistent.

int* OSInstance::getObjectiveCoefficientNumbers

(

)

Get objective coefficient number.

One number for each objective.

Returns:

an integer array of size of which is equal to number of objectives, each element of the array is the number of nonzero coefficients in that objective function, null if no objectives.

Exceptions:

Exception

if the elements in objectives are logically inconsistent.

double* OSInstance::getObjectiveConstants

(

)

Get objective constants.

One constant for each objective.

Returns:

a double array of objective constants, null if no objectives.

Exceptions:

Exception

if the elements in objectives are logically inconsistent.

double* OSInstance::getObjectiveWeights

(

)

Get objective weights.

One weight for each objective.

Returns:

a double array of objective weights, null if no objectives.

Exceptions:

Exception

if the elements in objectives are logically inconsistent.

SparseVector** OSInstance::getObjectiveCoefficients

(

)

Get objective coefficients.

One set of objective coefficients for each objective.

See also:

org.optimizationservices.oscommon.datastructure.SparseVector

Returns:

an array of objective coefficients, null if objective coefficients. Each member of the array is of type ObjectiveCoefficients. The ObjectiveCoefficients class contains two arrays: variableIndexes is an integer array and values is a double array of coefficient values.

Exceptions:

Exception

if the elements in objectives are logically inconsistent.

double** OSInstance::getDenseObjectiveCoefficients

(

)

getDenseObjectiveCoefficients.

Returns:

an vector of pointers, each pointer points to a dense vector of ObjectiveCoefficients.

int OSInstance::getConstraintNumber

(

)

Get constraint number.

Returns:

constraint number.

std::string* OSInstance::getConstraintNames

(

)

Get constraint names.

Returns:

a std::string array of constraint names, null if no constraint names.

Exceptions:

Exception

if the elements in constraints are logically inconsistent.

double* OSInstance::getConstraintLowerBounds

(

)

Get constraint lower bounds.

Returns:

a double array of constraint lower bounds, null if no constraints.

Exceptions:

Exception

if the elements in constraints are logically inconsistent.

double* OSInstance::getConstraintUpperBounds

(

)

Get constraint upper bounds.

Returns:

a double array of constraint upper bounds, null if constraints.

Exceptions:

Exception

if the elements in constraints are logically inconsistent.

char* OSInstance::getConstraintTypes

(

)

Get constraint types.

• R for range constraint lb <= constraint <= ub
• L for less than constraint -INF <= con <= ub or con <= ub
• G for greater than constraint lb <= con <= INF or con >= lb
• E for equal to constraint lb <= con <= ub where lb = ub or con = lb/ub
• U for unconstrained constraint -INF <= con <= INF

Returns:

a char array of constraint types, null if constraints.

Exceptions:

Exception

if the elements in constraints are logically inconsistent.

int OSInstance::getLinearConstraintCoefficientNumber

(

)

Get number of specified (usually nonzero) linear constraint coefficient values.

Returns:

number of specified (usually nonzero) linear constraint coefficient values.

bool OSInstance::getLinearConstraintCoefficientMajor

(

)

Get whether the constraint coefficients is in column major (true) or row major (false).

Returns:

whether the constraint coefficients is in column major (true) or row major (false).

Exceptions:

Exception

if the elements in linear constraint coefficients are logically inconsistent.

SparseMatrix* OSInstance::getLinearConstraintCoefficientsInColumnMajor

(

)

Get linear constraint coefficients in column major.

Returns:

a sparse matrix reprsentation of linear constraint coefficients in column major, null if no linear constraint coefficients.

Exceptions:

Exception

if the elements in linear constraint coefficients are logically inconsistent.

See also:

org.optimizationservices.oscommon.datastructure.SparseMatrix

SparseMatrix* OSInstance::getLinearConstraintCoefficientsInRowMajor

(

)

Get linear constraint coefficients in row major.

Returns:

a sparse matrix reprsentation of linear constraint coefficients in row major, null if no linear constraint coefficients.

Exceptions:

Exception

if the elements in linear constraint coefficients are logically inconsistent.

See also:

org.optimizationservices.oscommon.datastructure.SparseMatrix

int OSInstance::getNumberOfQuadraticTerms

(

)

Get the number of specified (usually nonzero) qTerms in the quadratic coefficients.

Returns:

qTerm number.

QuadraticTerms* OSInstance::getQuadraticTerms

(

)

Get all the quadratic terms in the instance.

Returns:

the QuadraticTerms data structure for all quadratic terms in the instance, null if no quadratic terms. The QuadraticTerms contains four arrays: rowIndexes, varOneIndexes, varTwoIndexes, coefficients.

Exceptions:

Exception

if the elements in quadratic coefficients are logically inconsistent.

See also:

org.optimizationservices.oscommon.datastructure.QuadraticTerms

int* OSInstance::getQuadraticRowIndexes

(

)

Get the indexes of rows which have a quadratic term.

Returns:

an integer pointer to the row indexes of rows with quadratic terms, objectives functions have index < 0 NULL if there are no quadratic terms.

int OSInstance::getNumberOfQuadraticRowIndexes

(

)

Get the number of rows which have a quadratic term.

Returns:

an integer which is the number of distinct rows (including obj) with quadratic terms,

int OSInstance::getNumberOfNonlinearExpressions

(

)

Get number of nonlinear expressions.

Returns:

the number of nonlinear expressions.

OSExpressionTree* OSInstance::getNonlinearExpressionTree

(

int

rowIdx

)

Get the expression tree for a given row index.

Returns:

an expression tree

OSExpressionTree* OSInstance::getNonlinearExpressionTreeMod

(

int

rowIdx

)

Get the expression tree for a given row index for the modified expression trees (quadratic terms added).

Returns:

an expression tree

std::vector<OSnLNode*> OSInstance::getNonlinearExpressionTreeInPostfix

(

int

rowIdx

)

Get the postfix tokens for a given row index.

Returns:

a vector of pointers to OSnLNodes in postfix, if rowIdx does not index a row with a nonlinear term throw an exception

std::vector<OSnLNode*> OSInstance::getNonlinearExpressionTreeModInPostfix

(

int

rowIdx

)

Get the postfix tokens for a given row index for the modified Expression Tree (quadratic terms added).

Returns:

a vector of pointers to OSnLNodes in postfix, if rowIdx does not index a row with a nonlinear term throw an exception

std::vector<OSnLNode*> OSInstance::getNonlinearExpressionTreeInPrefix

(

int

rowIdx

)

Get the prefix tokens for a given row index.

Returns:

a vector of pointers to OSnLNodes in prefix, if rowIdx does not index a row with a nonlinear term throw an exception

std::vector<OSnLNode*> OSInstance::getNonlinearExpressionTreeModInPrefix

(

int

rowIdx

)

Get the prefix tokens for a given row index for the modified Expression Tree (quadratic terms added).

Returns:

a vector of pointers to OSnLNodes in prefix, if rowIdx does not index a row with a nonlinear term throw an exception

int OSInstance::getNumberOfNonlinearObjectives

(

)

Returns:

the number of Objectives with a nonlinear term

int OSInstance::getNumberOfNonlinearConstraints

(

)

Returns:

the number of Constraints with a nonlinear term

std::map<int, OSExpressionTree* > OSInstance::getAllNonlinearExpressionTrees

(

)

Returns:

a map: the key is the row index and the value is the corresponding expression tree

std::map<int, OSExpressionTree* > OSInstance::getAllNonlinearExpressionTreesMod

(

)

Returns:

a map: the key is the row index and the value is the corresponding expression tree

int* OSInstance::getNonlinearExpressionTreeIndexes

(

)

Get all the nonlinear expression tree indexes, i.e.

indexes of rows (objectives or constraints) that contain nonlinear expressions.

Returns:

a pointer to an integer array of nonlinear expression tree indexes.

int OSInstance::getNumberOfNonlinearExpressionTreeIndexes

(

)

Get the number of unique Nonlinear expression tree indexes.

Returns:

the number of unique nonlinear expression tree indexes.

int* OSInstance::getNonlinearExpressionTreeModIndexes

(

)

Get all the nonlinear expression tree indexes, i.e.

indexes of rows (objetives or constraints) that contain nonlinear expressions after modifying the expression tree to contain quadratic terms.

Returns:

a pointer to an integer array of nonlinear expression tree indexes (including quadratic terms).

int OSInstance::getNumberOfNonlinearExpressionTreeModIndexes

(

)

Get the number of unique Nonlinear expression tree indexes after modifying the expression tree to contain quadratic terms.

Returns:

the number of unique nonlinear expression tree indexes (including quadratic terms).

std::string OSInstance::getTimeDomainFormat

(

)

Get the format of the time domain ("stages"/"interval").

Returns:

the format of the time domain.

int OSInstance::getTimeDomainStageNumber

(

)

Get the number of stages that make up the time domain.

Returns:

the number of time stages.

std::string* OSInstance::getTimeDomainStageNames

(

)

Get the names of the stages (NULL or empty string ("") if a stage has not been given a name.

Returns:

the names of time stages.

int* OSInstance::getTimeDomainStageNumberOfVariables

(

)

Get the number of variables contained in each time stage.

Returns:

a vector of size numberOfStages.

int* OSInstance::getTimeDomainStageNumberOfConstraints

(

)

Get the number of constraints contained in each time stage.

Returns:

a vector of size numberOfStages.

int* OSInstance::getTimeDomainStageNumberOfObjectives

(

)

Get the number of objectives contained in each time stage.

Returns:

a vector of size numberOfStages.

int** OSInstance::getTimeDomainStageVarList

(

)

Get the list of variables in each stage.

Returns:

one array of integers for each stage.

int** OSInstance::getTimeDomainStageConList

(

)

Get the list of constraints in each stage.

Returns:

one array of integers for each stage.

int** OSInstance::getTimeDomainStageObjList

(

)

Get the list of objectives in each stage.

Returns:

one array of integers for each stage.

double OSInstance::getTimeDomainIntervalStart

(

)

Get the start for the time domain interval.

Returns:

start end of the time interval.

double OSInstance::getTimeDomainIntervalHorizon

(

)

Get the horizon for the time domain interval.

Returns:

the end of the time interval.

bool OSInstance::setInstanceSource

(

std::string

source

)

set the instance source.

Parameters:

source

holds the instance source.

Returns:

whether the instance source is set successfully.

bool OSInstance::setInstanceDescription

(

std::string

description

)

set the instance description.

Parameters:

description

holds the instance description.

Returns:

whether the instance description is set successfully.

bool OSInstance::setInstanceName

(

std::string

name

)

set the instance name.

Parameters:

name

holds the instance name.

Returns:

whether the instance name is set successfully.

bool OSInstance::setVariableNumber

(

int

number

)

set the variable number.

Parameters:

number

holds the variable number.

Returns:

whether the variable number is set successfully.

bool OSInstance::addVariable	(	int	index,
		std::string	name,
		double	lowerBound,
		double	upperBound,
		char	type
	)

add a variable.

In order to use the add method, the setVariableNumber must first be called so that the variable number is known ahead of time to assign appropriate memory. If a variable with the given variable index already exists, the old variable will be replaced.

Parameters:

	index	holds the variable index. It is required.
	name	holds the variable name; use null or empty std::string ("") if no variable name.
	lowerBound	holds the variable lower bound; use Double.NEGATIVE_INFINITY if no lower bound.
	upperBound	holds the variable upper bound; use Double.POSITIVE_INFINITY if no upper bound.
	type	holds the variable type character, B for Binary, I for Integer, S for String, C or any other char for Continuous)
	init	holds the double variable initial value; use Double.NaN if no initial value -- deprecated
	initString	holds the std::string variable initial value; use null or empty std::string ("") if no initial std::string value -- deprecated

Returns:

whether the variable is added successfully.

bool OSInstance::setVariables	(	int	number,
		std::string *	names,
		double *	lowerBounds,
		double *	upperBounds,
		char *	types
	)

set all the variable related elements.

All the previous variable-related elements will be deleted.

Parameters:

	number	holds the number of variables. It is required.
	names	holds a std::string array of variable names; use null if no variable names.
	lowerBounds	holds a double array of variable lower bounds; use null if all lower bounds are 0; use Double.NEGATIVE_INFINITY if no lower bound for a specific variable in the array.
	upperBounds	holds a double array of variable upper bounds; use null if no upper bounds; use Double.POSITIVE_INFINITY if no upper bound for a specific variable in the array.
	types	holds a char array of variable types; use null if all variables are continuous; for a specfic variable in the array use B for Binary, I for Integer, S for String, C or any other char for Continuous,)
	inits	holds a double array of varible initial values; use null if no initial values. -- deprecated
	initsString	holds a std::string array of varible initial values; use null if no initial std::string values. -- deprecated

Returns:

whether the variables are set successfully.

bool OSInstance::setObjectiveNumber

(

int

number

)

set the objective number.

Parameters:

number

holds the objective number.

Returns:

whether the objective number is set successfully.

bool OSInstance::addObjective	(	int	index,
		std::string	name,
		std::string	maxOrMin,
		double	constant,
		double	weight,
		SparseVector *	objectiveCoefficients
	)

add an objective.

In order to use the add method, the setObjectiveNumber must first be called so that the objective number is known ahead of time to assign appropriate memory. If a objective with the given objective index already exists, the old objective will be replaced. Objective index will start from -1, -2, -3, ... down, with -1 corresponding to the first objective.

Parameters:

	index	holds the objective index. Remember the first objective index is -1, second -2, ...
	name	holds the objective name; use null or empty std::string ("") if no objective name.
	maxOrMin	holds the objective sense or direction; it can only take two values: "max" or "min".
	constant	holds the objective constant; use 0.0 if no objective constant.
	weight	holds the objective weight; use 1.0 if no objective weight.
	objectiveCoefficients	holds the objective coefficients (null if no objective coefficients) in a sparse representation that holds two arrays: index array and a value array.

Returns:

whether the objective is added successfully.

bool OSInstance::setObjectives	(	int	number,
		std::string *	names,
		std::string *	maxOrMins,
		double *	constants,
		double *	weights,
		SparseVector **	objectitiveCoefficients
	)

set all the objectives related elements.

All the previous objective-related elements will be deleted.

Parameters:

	number	holds the number of objectives. It is required.
	names	holds a std::string array of objective names; use null if no objective names.
	maxOrMins	holds a std::string array of objective objective senses or directions: "max" or "min"; use null if all objectives are "min".
	constants	holds a double array of objective constants; use null if all objective constants are 0.0.
	weights	holds a double array of objective weights; use null if all objective weights are 1.0.
	objectitiveCoefficients	holds an array of objective coefficients, (null if no objective have any coefficeints) For each objective, the coefficients are stored in a sparse representation that holds two arrays: index array and a value array. If for a specific objective, there are no objecitve coefficients, use null for the corresponding array member.

Returns:

whether the objectives are set successfully.

bool OSInstance::setConstraintNumber

(

int

number

)

set the constraint number.

Parameters:

number

holds the constraint number.

Returns:

whether the constraint number is set successfully.

bool OSInstance::addConstraint	(	int	index,
		std::string	name,
		double	lowerBound,
		double	upperBound,
		double	constant
	)

add a constraint.

In order to use the add method, the setConstraintNumber must first be called so that the constraint number is known ahead of time to assign appropriate memory. If a constraint with the given constraint index already exists, the old constraint will be replaced.

Parameters:

	index	holds the constraint index. It is required.
	name	holds the constraint name; use null or empty std::string ("") if no constraint name.
	lowerBound	holds the constraint lower bound; use Double.NEGATIVE_INFINITY if no lower bound.
	upperBound	holds the constraint upper bound; use Double.POSITIVE_INFINITY if no upper bound.

Returns:

whether the constraint is added successfully.

bool OSInstance::setConstraints	(	int	number,
		std::string *	names,
		double *	lowerBounds,
		double *	upperBounds,
		double *	constants
	)

set all the constraint related elements.

All the previous constraint-related elements will be deleted.

Parameters:

	number	holds the number of constraints. It is required.
	names	holds a std::string array of constraint names; use null if no constraint names.
	lowerBounds	holds a double array of constraint lower bounds; use null if no lower bounds; use Double.NEGATIVE_INFINITY if no lower bound for a specific constraint in the array.
	upperBounds	holds a double array of constraint upper bounds; use null if no upper bounds; use Double.POSITIVE_INFINITY if no upper bound for a specific constraint in the array.

Returns:

whether the constraints are set successfully.

bool OSInstance::setLinearConstraintCoefficients	(	int	numberOfValues,
		bool	isColumnMajor,
		double *	values,
		int	valuesBegin,
		int	valuesEnd,
		int *	indexes,
		int	indexesBegin,
		int	indexesEnd,
		int *	starts,
		int	startsBegin,
		int	startsEnd
	)

set linear constraint coefficients

Parameters:

	numberOfValues	holds the number of specified coefficient values (usually nonzero) in the coefficient matrix.
	isColumnMajor	holds whether the coefficient matrix is stored in column major (true) or row major (false).
	values	holds a double array coefficient values in the matrix.
	valuesBegin	holds the begin index of the values array to copy from (usually 0).
	valuesEnd	holds the end index of the values array to copy till (usually values.lenght - 1).
	indexes	holds an integer array column/row indexes for each value in the values array.
	indexesBegin	holds the begin index of the indexes array to copy from (usually 0).
	indexesEnd	holds the end index of the indexes array to copy till (usually indexes.lenght - 1).
	starts	holds an integer array start indexes in the matrix; the first value of starts should always be 0.
	startsBegin	holds the begin index of the starts array to copy from (usually 0).
	startsEnd	holds the end index of the starts array to copy till (usually starts.lenght - 1).

Returns:

whether the linear constraint coefficients are set successfully.

bool OSInstance::setQuadraticTerms	(	int	number,
		int *	rowIndexes,
		int *	varOneIndexes,
		int *	varTwoIndexes,
		double *	coefficients,
		int	begin,
		int	end
	)

set quadratic terms

Parameters:

	number	holds the number of quadratic terms.
	rowIndexes	holds an integer array of row indexes of all the quadratic terms. A negative integer corresponds to an objective row, e.g. -1 for 1st objective and -2 for 2nd.
	varOneIndexes	holds an integer array of the first varialbe indexes of all the quadratic terms.
	varTwoIndexes	holds an integer array of the second varialbe indexes of all the quadratic terms.
	coefficients	holds a double array all the quadratic term coefficients.
	begin	holds the begin index of all the arrays to copy from (usually = 0).
	end	holds the end index of all the arrays to copy till (usually = array length -1).

Returns:

whether the quadratic terms are set successfully.

bool OSInstance::setQuadraticTermsInNonlinearExpressions	(	int	number,
		int *	rowIndexes,
		int *	varOneIndexes,
		int *	varTwoIndexes,
		double *	coefficients
	)

set quadratic terms in nonlinearExpressions

Parameters:

	number	holds the number of quadratic terms.
	rowIndexes	holds an integer array of row indexes of all the quadratic terms. A negative integer corresponds to an objective row, e.g. -1 for 1st objective and -2 for 2nd.
	varOneIndexes	holds an integer array of the first varialbe indexes of all the quadratic terms.
	varTwoIndexes	holds an integer array of the second varialbe indexes of all the quadratic terms.
	coefficients	holds a double array all the quadratic term coefficients.

Returns:

whether the quadratic terms are set successfully.

bool OSInstance::initializeNonLinearStructures

(

)

Initialize the data structures for the nonlinear API.

Returns:

true if we have initialized the nonlinear data strucutres.

double OSInstance::calculateFunctionValue	(	int	idx,
		double *	x,
		bool	new_x
	)

Calculate the function value for function (constraint or objective) indexed by idx.

Parameters:

	idx	is the index on the constraint (0, 1, 2, 3, ...) or objective function (-1, -2, -3, ...).
	x	is a pointer (double array) to the current variable values
	new_x	is false if any evaluation method was previously called for the current x has been evaluated for the current iterate x use a value of false if not sure

Returns:

the function value as a double.

double* OSInstance::calculateAllConstraintFunctionValues	(	double *	x,
		double *	objLambda,
		double *	conLambda,
		bool	new_x,
		int	highestOrder
	)

Calculate all of the constraint function values.

Parameters:

	x	is a pointer (double array) to the current variable values
	objLambda	is the Lagrange multiplier on the objective function
	conLambda	is pointer (double array) of Lagrange multipliers on the constratins
	new_x	is false if any evaluation method was previously called for the current x for the current iterate
	highestOrder	is the highest order of the derivative being calculated

Returns:

a double array of constraint function values -- the size of the array is equal to getConstraintNumber().

double* OSInstance::calculateAllConstraintFunctionValues	(	double *	x,
		bool	new_x
	)

Calculate all of the constraint function values, we are overloading this function and this version of the method will not use any AD and will evaluate function values from the OS Expression Tree.

Parameters:

	x	is a pointer (double array) to the current variable values
	new_x	is false if any evaluation method was previously called for the current iterate

Returns:

a double array of constraint function values -- the size of the array is equal to getConstraintNumber().

double* OSInstance::calculateAllObjectiveFunctionValues	(	double *	x,
		double *	objLambda,
		double *	conLambda,
		bool	new_x,
		int	highestOrder
	)

Calculate all of the objective function values.

Parameters:

	x	is a pointer (double array) to the current variable values
	objLambda	is the Lagrange multiplier on the objective function
	conLambda	is pointer (double array) of Lagrange multipliers on the constratins
	new_x	is false if any evaluation method was previously called for the current iterate
	highestOrder	is the highest order of the derivative being calculated

Returns:

a double array of objective function values -- the size of the array is equal to getObjectiveNumber().

double* OSInstance::calculateAllObjectiveFunctionValues	(	double *	x,
		bool	new_x
	)

Calculate all of the objective function values, we are overloading this function and this version of the method will not use any AD and will evaluate function values from the OS Expression Tree.

Parameters:

	x	is a pointer (double array) to the current variable values
	new_x	is false if any evaluation method was previously called for the current iterate

Returns:

a double array of objective function values -- the size of the array is equal to getObjectiveNumber().

SparseJacobianMatrix* OSInstance::calculateAllConstraintFunctionGradients	(	double *	x,
		double *	objLambda,
		double *	conLambda,
		bool	new_x,
		int	highestOrder
	)

Calculate the gradient of all constraint functions.

Parameters:

	x	is a pointer (double array) to the current variable values
	objLambda	is the Lagrange multiplier on the objective function
	conLambda	is pointer (double array) of Lagrange multipliers on the constratins
	new_x	is false if any evaluation method was previously called for the current iterate
	highestOrder	is the highest order of the derivative being calculated

Returns:

a pointer a SparseJacobianMatrix.

SparseVector* OSInstance::calculateConstraintFunctionGradient	(	double *	x,
		double *	objLambda,
		double *	conLambda,
		int	idx,
		bool	new_x,
		int	highestOrder
	)

Calculate the gradient of the constraint function indexed by idx.

Parameters:

	x	is a pointer (double array) to the current variable values
	objLambda	is the Lagrange multiplier on the objective function
	conLambda	is pointer (double array) of Lagrange multipliers on the constratins idx is the index of the constraint function gradient
	new_x	is false if any evaluation method was previously called for the current iterate
	highestOrder	is the highest order of the derivative being calculated

Returns:

a pointer to a sparse vector of doubles.

SparseVector* OSInstance::calculateConstraintFunctionGradient	(	double *	x,
		int	idx,
		bool	new_x
	)

Calculate the gradient of the constraint function indexed by idx this function is overloaded.

Parameters:

	x	is a pointer (double array) to the current variable values idx is the index of the constraint function gradient
	new_x	is false if any evaluation method was previously called for the current iterate
	highestOrder	is the highest order of the derivative being calculated

Returns:

a pointer to a sparse vector of doubles.

double** OSInstance::calculateAllObjectiveFunctionGradients	(	double *	x,
		double *	objLambda,
		double *	conLambda,
		bool	new_x,
		int	highestOrder
	)

Calculate the gradient of all objective functions.

Parameters:

	x	is a pointer (double array) to the current variable values
	objLambda	is the Lagrange multiplier on the objective function
	conLambda	is pointer (double array) of Lagrange multipliers on the constratins
	new_x	is false if any evaluation method was previously called for the current iterate
	highestOrder	is the highest order of the derivative being calculated

Returns:

an array of pointer to dense objective function gradients.

double* OSInstance::calculateObjectiveFunctionGradient	(	double *	x,
		double *	objLambda,
		double *	conLambda,
		int	objIdx,
		bool	new_x,
		int	highestOrder
	)

Calculate the gradient of the objective function indexed by objIdx.

Parameters:

	x	is a pointer (double array) to the current variable values
	objLambda	is the Lagrange multiplier on the objective function
	conLambda	is pointer (double array) of Lagrange multipliers on the constratins objIdx is the index of the objective function being optimized
	new_x	is false if any evaluation method was previously called for the current iterate
	highestOrder	is the highest order of the derivative being calculated

Returns:

a pointer to a dense vector of doubles.

double* OSInstance::calculateObjectiveFunctionGradient	(	double *	x,
		int	objIdx,
		bool	new_x
	)

Calculate the gradient of the objective function indexed by objIdx this function is overloaded.

Parameters:

	x	is a pointer (double array) to the current variable values
	objIdx	is the index of the objective function being optimized
	new_x	is false if any evaluation method was previously called for the current iterate

Returns:

a pointer to a dense vector of doubles.

SparseHessianMatrix* OSInstance::calculateLagrangianHessian	(	double *	x,
		double *	objLambda,
		double *	conLambda,
		bool	new_x,
		int	highestOrder
	)

Calculate the Hessian of the Lagrangian Expression Tree This method will build the CppAD expression tree for only the first iteration Use this method on if the value of x does not affect the operations sequence.

Parameters:

	x	is a pointer (double array) to the current variable values
	objLambda	is the Lagrange multiplier on the objective function
	conLambda	is pointer (double array) of Lagrange multipliers on the constratins
	new_x	is false if any evaluation method was previously called for the current iterate
	highestOrder	is the highest order of the derivative being calculated

Returns:

a pointer a SparseHessianMatrix. Each array member corresponds to one constraint gradient.

SparseHessianMatrix* OSInstance::calculateHessian	(	double *	x,
		int	idx,
		bool	new_x
	)

Calculate the Hessian of a constraint or objective function.

Parameters:

	x	is a pointer (double array) to the current variable values
	new_x	is false if any evaluation method was previously called for the current iterate idx is the index of the either a constraint or objective function Hessian

Returns:

a pointer a SparseVector. Each array member corresponds to one constraint gradient.

bool OSInstance::getSparseJacobianFromColumnMajor

(

)

Returns:

true if successful in generating the constraints gradient.

bool OSInstance::getSparseJacobianFromRowMajor

(

)

Returns:

true if successful in generating the constraints gradient.

OSExpressionTree* OSInstance::getLagrangianExpTree

(

)

Returns:

a pointer to the ExpressionTree for the Lagrangian function of current instance we only take the Lagrangian of the rows with nonlinear terms

std::map<int, int> OSInstance::getAllNonlinearVariablesIndexMap

(

)

Returns:

a pointer to a map of the indices of all of the variables that appear in the Lagrangian function

SparseHessianMatrix* OSInstance::getLagrangianHessianSparsityPattern

(

)

Returns:

a pointer to a SparseHessianMatrix with the nonzero structure of the Lagrangian Expression Tree

bool OSInstance::addQTermsToExressionTree

(

)

Returns:

true if successful in adding the qTerms to the ExpressionTree.

SparseJacobianMatrix* OSInstance::getJacobianSparsityPattern

(

)

Returns:

pointer to a SparseJacobianMatrix.

void OSInstance::duplicateExpressionTreesMap

(

)

duplicate the map of expression trees.

bool OSInstance::createOSADFun

(

std::vector< double >

vdX

)

Create the a CppAD Function object: this is a function where the domain is the set of variables for the problem and the range is the objective function plus constraints.

Parameters:

vdX

is a vector of doubles holding the current primal variable values the size of x should equal instanceData->variables->numberOfVariables

Returns:

if successfully created

std::vector<double> OSInstance::forwardAD	(	int	p,
		std::vector< double >	vdX
	)

Perform an AD forward sweep.

Parameters:

	p	is the highest order Taylor coefficient
	vdX	is a vector of doubles of the current primal variable values the size of vdX m_iNumberOfNonlinearVariables

Returns:

a double vector equal to the dimension of the range space the result of the forward p sweep

std::vector<double> OSInstance::reverseAD	(	int	p,
		std::vector< double >	vdlambda
	)

Perform an AD reverse sweep.

Parameters:

	p	is the order of the sweep
	vdlambda	is a vector of doubles of the current dual (lagrange) variable values the size of lambda should equal number of objective functions plus number of constraints

Returns:

a double vector equal to the n*p

int OSInstance::getADSparsityHessian

(

)

end revised AD code

Call the AD routine to fill in m_vbLagHessNonz and determine the nonzeros.

Returns:

the number of nonzeros in the Hessian

bool OSInstance::getIterateResults	(	double *	x,
		double *	objLambda,
		double *	conLambda,
		bool	new_x,
		int	highestOrder
	)

end revised AD code

Get the information for each iteration. Get the functions values, Jacobian and Hessian of the Lagrangian

Parameters:

	x	is a pointer of doubles of primal values for the current iteration
	objLambda	is is a pointer of doubles of the current dual (Lagrange) multipliers on the objective functions
	conLambda	is a pointer of doubles of the current dual (Lagrange) multipliers on the constraints
	new_x	is false if any evaluation method was previously called
	highestOrder	is the highest order derivative to be calculated

Returns:

true if successful

bool OSInstance::getZeroOrderResults	(	double *	x,
		double *	objLambda,
		double *	conLambda
	)

Calculate function values.

Parameters:

	x	is a pointer of doubles of primal values for the current iteration
	objLambda	is is a pointer of doubles of the current dual (Lagrange) multipliers on the objective functions
	conLambda	is a pointer of doubles of the current dual (Lagrange) multipliers on the constraints

Returns:

true if successful

bool OSInstance::getFirstOrderResults	(	double *	x,
		double *	objLambda,
		double *	conLambda
	)

Calculate first derivatives.

Parameters:

	x	is a pointer of doubles of primal values for the current iteration
	objLambda	is is a pointer of doubles of the current dual (Lagrange) multipliers on the objective functions
	conLambda	is a pointer of doubles of the current dual (Lagrange) multipliers on the constraints

Returns:

true if successful

bool OSInstance::getSecondOrderResults	(	double *	x,
		double *	objLambda,
		double *	conLambda
	)

Calculate second derivatives.

Parameters:

	x	is a pointer of doubles of primal values for the current iteration
	objLambda	is is a pointer of doubles of the current dual (Lagrange) multipliers on the objective functions
	conLambda	is a pointer of doubles of the current dual (Lagrange) multipliers on the constraints

Returns:

true if successful

bool OSInstance::initForAlgDiff

(

)

This should be called by nonlinear solvers using callback functions.

initForAlgDiff will initialize the correct nonlinear structures in preparation for using the algorithmic differentiation routines.

Returns:

true if successful

bool OSInstance::initObjGradients

(

)

This should be called by initForAlgDiff().

initObjGradients will initialize the objective function gradients to be equal to the coefficients given in the <coef> section of the OSiL instance

Returns:

true if successful

bool OSInstance::setTimeDomain

(

std::string

format

)

This sets the format of the time domain ("stages"/"interval"/"none").

bool OSInstance::setTimeDomainStages	(	int	number,
		std::string *	names
	)

This sets the number (and optionally names) of the time stages.

bool OSInstance::setTimeDomainStageVariablesOrdered	(	int	numberOfStages,
		int *	numberOfVariables,
		int *	startIdx
	)

This sets the variables associated with each time domain stage in temporal order.

(I.e., for each stage numberOfVariables gives the number of variables accociated with this stage and startIdx gives the first variable in this stage.)

bool OSInstance::setTimeDomainStageVariablesUnordered	(	int	numberOfStages,
		int *	numberOfVariables,
		int **	varIndex
	)

This sets the variables associated with each time domain stage in srbitrary order.

(I.e., for each stage numberOfVariables gives the number of variables accociated with this stage and varIndex[i] gives the index of each variable in stage[i].)

bool OSInstance::setTimeDomainStageConstraintsOrdered	(	int	numberOfStages,
		int *	numberOfConstraints,
		int *	startIdx
	)

This sets the constraints associated with each time domain stage in temporal order.

(I.e., for each stage numberOfConstraints gives the number of constraints accociated with this stage and startIdx gives the first constraint in this stage.)

bool OSInstance::setTimeDomainStageConstraintsUnordered	(	int	numberOfStages,
		int *	numberOfConstraints,
		int **	conIndex
	)

This sets the constraints associated with each time domain stage in srbitrary order.

(I.e., for each stage numberOfConstraints gives the number of constraints accociated with this stage and conIndex[i] gives the index of each constraint in stage[i].)

bool OSInstance::setTimeDomainStageObjectivesOrdered	(	int	numberOfStages,
		int *	numberOfObjectives,
		int *	startIdx
	)

This sets the objectives associated with each time domain stage in temporal order.

(I.e., for each stage numberOfObjectives gives the number of objectives accociated with this stage and startIdx gives the first objective in this stage.)

bool OSInstance::setTimeDomainStageObjectivesUnordered	(	int	numberOfStages,
		int *	numberOfObjectives,
		int **	varIndex
	)

This sets the objectives associated with each time domain stage in arbitrary order.

(I.e., for each stage numberOfObjectives gives the number of objectives accociated with this stage and objIndex[i] gives the index of each objective in stage[i].)

bool OSInstance::setTimeDomainInterval	(	double	start,
		double	horizon
	)

This sets the start and end of the time interval.

---

Member Data Documentation

GeneralFileHeader* OSInstance::instanceHeader

the instanceHeader is implemented as a general file header object to allow sharing of classes between schemas

Definition at line 2275 of file OSInstance.h.

InstanceData * OSInstance::instanceData

A pointer to an InstanceData object.

Definition at line 2278 of file OSInstance.h.

bool OSInstance::bVariablesModified

bVariablesModified is true if the variables data has been modified.

Definition at line 2288 of file OSInstance.h.

bool OSInstance::bObjectivesModified

bObjectivesModified is true if the objective function data has been modified.

Definition at line 2293 of file OSInstance.h.

bool OSInstance::bConstraintsModified

bConstraintsModified is true if the constraints data has been modified.

Definition at line 2298 of file OSInstance.h.

bool OSInstance::bAMatrixModified

bAMatrixModified is true if the A matrix data has been modified.

Definition at line 2303 of file OSInstance.h.

std::string OSInstance::m_sInstanceName [private]

------- data items for InstanceHeader -------

m_sInstanceName holds the instance name.

Definition at line 2310 of file OSInstance.h.

std::string OSInstance::m_sInstanceSource [private]

m_sInstanceSource holds the instance source.

Definition at line 2314 of file OSInstance.h.

std::string OSInstance::m_sInstanceDescription [private]

m_sInstanceDescription holds the instance description.

Definition at line 2318 of file OSInstance.h.

std::string OSInstance::m_sInstanceCreator [private]

m_sInstanceSource holds the instance source.

Definition at line 2322 of file OSInstance.h.

std::string OSInstance::m_sInstanceLicence [private]

m_sInstanceDescription holds the instance fileCreator info.

Definition at line 2326 of file OSInstance.h.

bool OSInstance::m_bProcessVariables [private]

------- data items for Variables -------

m_bProcessVariables holds whether the variables are processed.

Definition at line 2333 of file OSInstance.h.

int OSInstance::m_iVariableNumber [private]

m_iVariableNumber holds the variable number.

Definition at line 2338 of file OSInstance.h.

int OSInstance::m_iNumberOfIntegerVariables [private]

m_iNumberOfIntegerVariables holds the number of integer variables.

Definition at line 2343 of file OSInstance.h.

int OSInstance::m_iNumberOfBinaryVariables [private]

m_iNumberOfBinaryVariables holds the number of binary variables.

Definition at line 2348 of file OSInstance.h.

int OSInstance::m_iNumberOfSemiContinuousVariables [private]

m_iNumberOfSemiContinuousVariables holds the number of semi-continuous variables.

Definition at line 2353 of file OSInstance.h.

int OSInstance::m_iNumberOfSemiIntegerVariables [private]

m_iNumberOfSemiIntegerVariables holds the number of semi-integer variables.

Definition at line 2358 of file OSInstance.h.

int OSInstance::m_iNumberOfStringVariables [private]

m_iNumberOfStringVariables holds the number of string-valued variables.

Definition at line 2363 of file OSInstance.h.

std::string * OSInstance::m_msVariableNames [private]

m_msVariableNames holds an array of variable names.

Definition at line 2368 of file OSInstance.h.

char * OSInstance::m_mcVariableTypes [private]

m_mcVariableTypes holds a char array of variable types (default = 'C').

m_mdVariableInitialValues holds a double array of the initial variable values.

(C for Continuous; B for Binary; I for Integer; S for String)

-- now deprecated m_msVariableInitialStringValues holds a std::string array of the initial variable values. -- now deprecated m_mcVariableTypes holds a char array of variable types (default = 'C'). (C for Continuous; B for Binary; I for Integer; S for String)

Definition at line 2374 of file OSInstance.h.

double * OSInstance::m_mdVariableLowerBounds [private]

m_mdVariableLowerBounds holds a double array of variable lower bounds (default = 0.0).

Definition at line 2379 of file OSInstance.h.

double * OSInstance::m_mdVariableUpperBounds [private]

m_mdVariableUpperBounds holds a double array of variable upper bounds (default = INF).

Definition at line 2384 of file OSInstance.h.

bool OSInstance::m_bProcessObjectives [private]

------- data items for Objectives -------

m_bProcessObjectives holds whether the objectives are processed.

Definition at line 2391 of file OSInstance.h.

int OSInstance::m_iObjectiveNumber [private]

m_iObjectiveNumber is the number of objective functions.

Definition at line 2396 of file OSInstance.h.

int OSInstance::m_iObjectiveNumberNonlinear [private]

m_iObjectiveNumber is the number of objective functions with a nonlinear term.

Definition at line 2401 of file OSInstance.h.

std::string * OSInstance::m_msObjectiveNames [private]

m_msObjectiveNames holds an array of objective names.

Definition at line 2406 of file OSInstance.h.

std::string * OSInstance::m_msMaxOrMins [private]

m_msMaxOrMins holds a std::string array of objective maxOrMins ("max" or "min").

Definition at line 2411 of file OSInstance.h.

int * OSInstance::m_miNumberOfObjCoef [private]

m_miNumberOfObjCoef holds an integer array of number of objective coefficients (default = 0).

m_miNumberOfObjCoef holds an integer array of number of objective coefficients (default = 0.0).

Definition at line 2416 of file OSInstance.h.

double * OSInstance::m_mdObjectiveConstants [private]

m_mdObjectiveConstants holds an array of objective constants (default = 0.0).

Definition at line 2421 of file OSInstance.h.

double * OSInstance::m_mdObjectiveWeights [private]

m_mdObjectiveWeights holds an array of objective weights (default = 1.0).

Definition at line 2426 of file OSInstance.h.

SparseVector ** OSInstance::m_mObjectiveCoefficients [private]

m_mObjectiveCoefficients holds an array of objective coefficients, one set of objective coefficients for each objective.

Definition at line 2432 of file OSInstance.h.

bool OSInstance::m_bGetDenseObjectives [private]

m_bGetDenseObjectives holds whether the dense objective functions are processed.

Definition at line 2437 of file OSInstance.h.

double ** OSInstance::m_mmdDenseObjectiveCoefficients [private]

m_mmdDenseObjectiveCoefficients holds an array of pointers, each pointer points to a vector of dense objective function coefficients

Definition at line 2443 of file OSInstance.h.

bool OSInstance::m_bProcessConstraints [private]

------- data items for Constraints -------

m_bProcessConstraints holds whether the constraints are processed.

Definition at line 2450 of file OSInstance.h.

int OSInstance::m_iConstraintNumber [private]

m_iConstraintNumber is the number of constraints.

Definition at line 2455 of file OSInstance.h.

int OSInstance::m_iConstraintNumberNonlinear [private]

m_iConstraintNumberNonlinear is the number of constraints that have a nonlinear term.

Definition at line 2460 of file OSInstance.h.

std::string * OSInstance::m_msConstraintNames [private]

m_msConstraintNames holds an array of constraint names.

Definition at line 2465 of file OSInstance.h.

double * OSInstance::m_mdConstraintLowerBounds [private]

m_mdConstraintLowerBounds holds an array of constraint lower bounds (default = -INF).

Definition at line 2470 of file OSInstance.h.

double * OSInstance::m_mdConstraintUpperBounds [private]

m_mdConstraintUpperBounds holds an array of constraint upper bounds (default = INF).

Definition at line 2475 of file OSInstance.h.

double * OSInstance::m_mdConstraintConstants [private]

m_mdConstraintConstants holds an array of constraint constants (default = 0.0).

Definition at line 2481 of file OSInstance.h.

char * OSInstance::m_mcConstraintTypes [private]

m_mcConstraintTypes holds a char array of constraint types (R for range; L for <=; G for >=; E for =; U for unconstrained)

Definition at line 2487 of file OSInstance.h.

bool OSInstance::m_bProcessLinearConstraintCoefficients [private]

------- data items for linear constraint coefficients -------

m_bProcessLinearConstraintCoefficients holds whether the linear constraint coefficients are processed.

m_bProcessLinearConstraintCoefficients holds whether the linear constraint coefficients have been processed.

Definition at line 2495 of file OSInstance.h.

int OSInstance::m_iLinearConstraintCoefficientNumber [private]

m_iLinearConstraintCoefficientNumber holds the number of specified (usually nonzero) linear constraint coefficient values.

Definition at line 2501 of file OSInstance.h.

bool OSInstance::m_bColumnMajor [private]

m_bColumnMajor holds whether the linear constraint coefficients are stored in column major (if m_bColumnMajor = true) or row major.

m_bColumnMajor holds whether the linear constraint coefficients are stored in column major.

Definition at line 2507 of file OSInstance.h.

SparseMatrix * OSInstance::m_linearConstraintCoefficientsInColumnMajor [private]

m_linearConstraintCoefficientsInColumnMajor holds the standard three-array data structure for linear constraint coefficients (starts, indexes and values) in column major.

m_linearConstraintCoefficientsInColumnMajor holds the standard 3 array data structure for linear constraint coefficients (starts, indexes and values) in column major.

Definition at line 2514 of file OSInstance.h.

SparseMatrix * OSInstance::m_linearConstraintCoefficientsInRowMajor [private]

m_linearConstraintCoefficientsInRowMajor holds the standard three-array data structure for linear constraint coefficients (starts, indexes and values) in row major.

m_linearConstraintCoefficientsInRowMajor holds the standard 3 array data structure for linear constraint coefficients (starts, indexes and values) in row major.

Definition at line 2521 of file OSInstance.h.

int OSInstance::m_iNumberOfQuadraticRowIndexes [private]

------- data items for quadratic coefficients -------

m_iNumberOfQuadraticRowIndexes holds the number of distinct rows and objectives with quadratic terms.

Definition at line 2528 of file OSInstance.h.

bool OSInstance::m_bQuadraticRowIndexesProcessed [private]

m_bQuadraticRowIndexesProcessed is true if getQuadraticRowIndexes() has been called.

Definition at line 2533 of file OSInstance.h.

int * OSInstance::m_miQuadRowIndexes [private]

m_miQuadRowIndexes is an integer pointer to the distinct row indexes with a quadratic term.

m_miQuadRowIndexes is an integer pointer to the distinct rows indexes with a quadratic term.

Definition at line 2538 of file OSInstance.h.

bool OSInstance::m_bProcessQuadraticTerms [private]

m_bProcessQuadraticTerms holds whether the quadratic terms are processed.

Definition at line 2543 of file OSInstance.h.

int OSInstance::m_iQuadraticTermNumber [private]

m_iQuadraticTermNumber holds the number of specified (usually nonzero) qTerms in the quadratic coefficients.

Definition at line 2549 of file OSInstance.h.

QuadraticTerms * OSInstance::m_quadraticTerms [private]

m_quadraticTerms holds the data structure for all the quadratic terms in the instance.

m_quadraticTerms the data structure for all the quadratic terms in the instance.

` (rowIdx, varOneIdx, varTwoIdx, coef)

Definition at line 2555 of file OSInstance.h.

bool OSInstance::m_bQTermsAdded [private]

m_bQTermsAdded is true if we added the quadratic terms to the expression tree

m_bQTermsAdded is true if we add the quadratic terms to the expression tree

Definition at line 2559 of file OSInstance.h.

int OSInstance::m_iNumberOfNonlinearExpressionTreeIndexes [private]

------- data items for nonlinear expressions -------

m_iNumberOfNonlinearExpressionTreeIndexes holds the number of distinct rows and objectives with nonlinear terms.

Definition at line 2567 of file OSInstance.h.

bool OSInstance::m_bNonlinearExpressionTreeIndexesProcessed [private]

m_bNonlinearExpressionTreeIndexesProcessed is true if getNonlinearExpressionTreeIndexes() has been called.

m_bNonlinearExpressionTreeIndexesProcessed is true if getNonlinearExpressionTreeIndexes has been called.

Definition at line 2573 of file OSInstance.h.

int * OSInstance::m_miNonlinearExpressionTreeIndexes [private]

m_miNonlinearExpressionTreeIndexes is an integer pointer to the distinct rows indexes in the nonlinear expression tree map.

Definition at line 2580 of file OSInstance.h.

int OSInstance::m_iNumberOfNonlinearExpressionTreeModIndexes [private]

m_iNumberOfNonlinearExpressionTreeModIndexes holds the number of distinct rows and objectives with nonlinear terms including quadratic terms added to the nonlinear expression trees.

Definition at line 2587 of file OSInstance.h.

bool OSInstance::m_bNonlinearExpressionTreeModIndexesProcessed [private]

m_bNonlinearExpressionTreeModIndexesProcessed is true if getNonlinearExpressionTreeModIndexes has been called.

Definition at line 2593 of file OSInstance.h.

int * OSInstance::m_miNonlinearExpressionTreeModIndexes [private]

m_miNonlinearExpressionTreeModIndexes is an integer pointer to the distinct rows indexes in the modified expression tree map.

Definition at line 2599 of file OSInstance.h.

bool OSInstance::m_binitForAlgDiff [private]

------- data items for automatic differentiation -------

m_binitForAlgDiff is true if initForAlgDiff() has been called.

Definition at line 2606 of file OSInstance.h.

unsigned int OSInstance::m_iNumberOfNonlinearVariables [private]

m_iNumberOfNonlinearVariables is the number of variables that appear in a nonlinear expression.

Definition at line 2612 of file OSInstance.h.

bool OSInstance::m_bProcessNonlinearExpressions [private]

m_bProcessNonlinearExpressions holds whether the nonlinear expressions are processed.

Definition at line 2617 of file OSInstance.h.

int OSInstance::m_iNonlinearExpressionNumber [private]

m_iNonlinearExpressionNumber holds the number of nonlinear expressions.

Definition at line 2622 of file OSInstance.h.

int * OSInstance::m_miNonlinearExpressionIndexes [private]

m_miNonlinearExpressionIndexes holds an integer array of nonlinear expression indexes, negative indexes correspond to objectives.

Definition at line 2628 of file OSInstance.h.

bool OSInstance::m_bProcessExpressionTrees [private]

m_bProcessExpressionTrees is true if the expression trees have been processed.

Definition at line 2633 of file OSInstance.h.

bool OSInstance::m_bProcessExpressionTreesMod [private]

m_bProcessExpressionTreesMod is true if the modified expression trees have been processed.

Definition at line 2638 of file OSInstance.h.

double * OSInstance::m_mdConstraintFunctionValues [private]

m_mdConstraintFunctionValues holds a double array of constraint function values -- the size of the array is equal to getConstraintNumber().

Definition at line 2644 of file OSInstance.h.

double * OSInstance::m_mdObjectiveFunctionValues [private]

m_mdObjectiveFunctionValues holds a double array of objective function values -- the size of the array is equal to getObjectiveNumber().

Definition at line 2650 of file OSInstance.h.

int OSInstance::m_iJacValueSize [private]

m_iJacValueSize is the number of nonzero partial derivates in the Jacobian.

Definition at line 2655 of file OSInstance.h.

int * OSInstance::m_miJacStart [private]

m_miJacStart holds a int array of starts for the Jacobian matrix in sparse form (row major).

Definition at line 2660 of file OSInstance.h.

int * OSInstance::m_miJacIndex [private]

m_miJacIndex holds a int array of variable indices for the Jacobian matrix in sparse form (row major).

Definition at line 2665 of file OSInstance.h.

double * OSInstance::m_mdJacValue [private]

m_mdJacValue holds a double array of partial derivatives for the Jacobian matrix in sparse form (row major).

Definition at line 2670 of file OSInstance.h.

int * OSInstance::m_miJacNumConTerms [private]

m_miJacNumConTerms holds a int array of the number of constant terms (gradient does not change) for the Jacobian matrix in sparse form (row major).

Definition at line 2676 of file OSInstance.h.

SparseJacobianMatrix * OSInstance::m_sparseJacMatrix [private]

m_sparseJacMatrix is the Jacobian matrix stored in sparse matrix format

Definition at line 2681 of file OSInstance.h.

int OSInstance::m_iHighestTaylorCoeffOrder [private]

m_iHighestTaylorCoeffOrder is the order of highest calculated Taylor coefficient

Definition at line 2687 of file OSInstance.h.

std::map<int, ScalarExpressionTree*> OSInstance::m_mapExpressionTrees [private]

m_mapExpressionTrees holds a hash map of scalar-valued expression tree pointers.

The key is the row index and the value is the (single) expression tree representing the nonlinear expression of that row.

Remarks:

For this to work all nonlinear expressions (including quadratic ones) must be combined into a single expression.

Definition at line 2697 of file OSInstance.h.

std::map< int, int > OSInstance::m_mapOSADFunRangeIndex [private]

m_mapOSADFunRangeIndex is an inverse of the previous map.

The key is the number of the scalar-valued expression tree, and the value is the row to which this tree belongs.

Definition at line 2703 of file OSInstance.h.

std::map<int, MatrixExpressionTree*> OSInstance::m_mapMatrixExpressionTrees [private]

m_mapMatrixExpressionTrees holds a hash map of matrix-valued expression tree pointers.

The key is the "row" index (multivariate cone objective or cone constraint) and the value is the (single) expression tree representing the expression of that row.

Remarks:

For this to work all matrix expressions (including linear and quadratic ones) must be combined into a single expression.

Definition at line 2713 of file OSInstance.h.

ScalarExpressionTree* OSInstance::m_LagrangianExpTree [private]

m_LagrangianExpTree is an ScalarExpressionTree object that is the expression tree for the Lagrangian function.

Definition at line 2719 of file OSInstance.h.

bool OSInstance::m_bLagrangianExpTreeCreated [private]

m_bLagrangianHessionCreated is true if a Lagrangian function for the Hessian has been created

Definition at line 2724 of file OSInstance.h.

SparseHessianMatrix * OSInstance::m_LagrangianSparseHessian [private]

m_LagrangianSparseHessian is the Hessian Matrix of the Lagrangian function in sparse format

Definition at line 2729 of file OSInstance.h.

bool OSInstance::m_bLagrangianSparseHessianCreated [private]

m_bLagrangianSparseHessianCreated is true if the sparse Hessian Matrix for the Lagrangian was created

Definition at line 2735 of file OSInstance.h.

std::map< int, int > OSInstance::m_mapAllNonlinearVariablesIndex [private]

m_mapAllNonlinearVariablesIndexMap is a map of the variables in the Lagrangian function

Definition at line 2740 of file OSInstance.h.

int * OSInstance::m_miNonLinearVarsReverseMap [private]

m_miNonLinearVarsReverseMap maps the nonlinear variable number back into the original variable space

Definition at line 2746 of file OSInstance.h.

bool OSInstance::m_bAllNonlinearVariablesIndex [private]

m_bAllNonlinearVariablesIndexMap is true if the map of the variables in the Lagrangian function has been constructed

Definition at line 2752 of file OSInstance.h.

std::map<int, ScalarExpressionTree*> OSInstance::m_mapExpressionTreesMod [private]

m_mapExpressionTreesMod holds a map of expression trees, with the key being the row index and value being the expression tree representing a modification of the nonlinear expression of that row.

We incorporate the linear and quadratic term for a variable into the corresponding expression tree before gradient and Hessian calculations

Definition at line 2761 of file OSInstance.h.

bool OSInstance::m_bOSADFunIsCreated [private]

m_bOSADFunIsCreated is true if we have created the OSInstanc OSAD Function

Definition at line 2768 of file OSInstance.h.

bool OSInstance::m_bCppADTapesBuilt [private]

is true if a CppAD Expresion Tree has been built for each row and objective with a nonlinear expression.

Definition at line 2774 of file OSInstance.h.

bool OSInstance::m_bCppADMustReTape [private]

is true if a CppAD Expresion Tree has an expression that can change depending on the value of the input, e.g.

an if statement -- false by default

Definition at line 2780 of file OSInstance.h.

bool OSInstance::m_bDuplicateExpressionTreesMap [private]

m_bDuplicateExpressionTreeMap is true if m_mapExpressionTrees was duplicated.

Definition at line 2785 of file OSInstance.h.

bool OSInstance::m_bNonLinearStructuresInitialized [private]

m_bNonLinearStructuresInitialized is true if initializeNonLinearStructures() has been called.

m_bNonLinearStructuresInitialized is true if initializeNonLinearStructures( ) has been called.

Definition at line 2790 of file OSInstance.h.

bool OSInstance::m_bSparseJacobianCalculated [private]

m_bSparseJacobianCalculated is true if getJacobianSparsityPattern() has been called.

Definition at line 2795 of file OSInstance.h.

std::map< int, std::vector< OSnLNode * > > OSInstance::m_mapExpressionTreesInPostfix [private]

m_mapExpressionTreesInPostfix holds a hash map of expression trees in postfix format, with the key being the row index and value being the expression tree representing the nonlinear expression of that row.

m_mapExpressionTrees holds a hash map of expression trees in postfix format, with the key being the row index and value being the expression tree representing the nonlinear expression of that row.

Definition at line 2802 of file OSInstance.h.

int OSInstance::m_iHighestOrderEvaluated [private]

m_iHighestOrderEvaluated is the highest order derivative of the current iterate

Definition at line 2808 of file OSInstance.h.

double ** OSInstance::m_mmdObjGradient [private]

m_mdObjGradient holds an array of pointers, each pointer points to gradient of one objective function (as a dense array of double)

m_mdObjGradient holds an array of pointers, each pointer points to gradient of each objective function

Definition at line 2814 of file OSInstance.h.

std::vector< double > OSInstance::m_vdX [private]

------- data vectors for nonlinear optimization -------

m_vdX is a vector of primal variables at each iteration

Definition at line 2821 of file OSInstance.h.

std::vector< double > OSInstance::m_vdYval [private]

m_vdYval is a vector of function values

Definition at line 2826 of file OSInstance.h.

std::vector< bool > OSInstance::m_vbLagHessNonz [private]

m_vbLagHessNonz is a boolean vector holding the nonzero pattern of the Lagrangian of the Hessian

Definition at line 2832 of file OSInstance.h.

std::vector< double > OSInstance::m_vdYjacval [private]

m_vdYval is a vector equal to a column or row of the Jacobian

Definition at line 2837 of file OSInstance.h.

std::vector< double > OSInstance::m_vdw [private]

m_vdYval is a vector of derivatives -- output from a reverse sweep

Definition at line 2842 of file OSInstance.h.

std::vector< double > OSInstance::m_vdLambda [private]

m_vdYval is a vector of Lagrange multipliers

Definition at line 2847 of file OSInstance.h.

std::vector< double > OSInstance::m_vdDomainUnitVec [private]

m_vdDomainUnitVec is a unit vector in the domain space

Definition at line 2852 of file OSInstance.h.

std::vector< double > OSInstance::m_vdRangeUnitVec [private]

m_vdRangeUnitVec is a unit vector in the range space

Definition at line 2857 of file OSInstance.h.

bool OSInstance::m_bProcessMatrices [private]

------- data items for matrices -------

m_bProcessMatrices holds whether the matrices have been processed.

Definition at line 2864 of file OSInstance.h.

int OSInstance::m_iMatrixNumber [private]

m_iMatrixNumber holds the number of matrices

Definition at line 2869 of file OSInstance.h.

ENUM_MATRIX_SYMMETRY* OSInstance::m_miMatrixSymmetry [private]

m_miMatrixSymmetry holds the symmetry property of each matrix.

Remarks:

for more information see the enumeration ENUM_MATRIX_SYMMETRY in OSParameters.h

Definition at line 2875 of file OSInstance.h.

ENUM_MATRIX_TYPE* OSInstance::m_miMatrixType [private]

m_miMatrixType holds the type of each matrix.

Remarks:

for more information see the enumeration ENUM_MATRIX_TYPE in OSParameters.h

Definition at line 2881 of file OSInstance.h.

int* OSInstance::m_miMatrixNumberOfColumns [private]

m_miMatrixNumberOfColumns holds the number of columns for each matrix.

Definition at line 2886 of file OSInstance.h.

int* OSInstance::m_miMatrixNumberOfRows [private]

m_miMatrixNumberOfRows holds the number of rows for each matrix.

Definition at line 2891 of file OSInstance.h.

std::string* OSInstance::m_msMatrixNames [private]

m_msMatrixNames holds the names of the matrices

Definition at line 2896 of file OSInstance.h.

OSMatrix** OSInstance::m_mMatrix [private]

m_mMatrix holds the list of constructors for each matrix.

Each solver interface must access the list of matrices, check that the data as given can be handled by the solver and perform whatever transformations are necessary to send the data to the solver.

Definition at line 2905 of file OSInstance.h.

int OSInstance::m_iMatrixVarNumber [private]

------- data items for matrix programming -------

m_iMatrixVarNumber holds the number of matrix variables

Definition at line 2956 of file OSInstance.h.

int OSInstance::m_iMatrixObjNumber [private]

m_iMatrixObjNumber holds the number of matrix objectives

Definition at line 2961 of file OSInstance.h.

int OSInstance::m_iMatrixConNumber [private]

m_iMatrixConNumber holds the number of matrix constraints

Definition at line 2966 of file OSInstance.h.

int OSInstance::m_iMatrixExpressionNumber [private]

m_iMatrixExpressionNumber holds the number of matrix expressions

Definition at line 2971 of file OSInstance.h.

bool OSInstance::m_bProcessTimeDomain [private]

------- data items for time domain -------

m_bProcessTimeDomain holds whether the time domain has been processed.

Definition at line 2978 of file OSInstance.h.

bool OSInstance::m_bProcessTimeStages [private]

m_bProcessTimeStages holds whether the time stages have been processed.

Definition at line 2983 of file OSInstance.h.

bool OSInstance::m_bProcessTimeInterval [private]

m_bProcessTimeInterval holds whether a time interval has been processed.

Definition at line 2988 of file OSInstance.h.

bool OSInstance::m_bFiniteTimeStages [private]

m_bFiniteTimeStages holds whether the time domain has the form of finite (discrete) stages.

Definition at line 2993 of file OSInstance.h.

int OSInstance::m_iNumberOfTimeStages [private]

m_iNumberOfTimeStages holds the number of discrete stages

Definition at line 2998 of file OSInstance.h.

std::string OSInstance::m_sTimeDomainFormat [private]

m_sTimeDomainFormat holds the format ("stages"/"interval") of the time domain.

Definition at line 3003 of file OSInstance.h.

std::string * OSInstance::m_msTimeDomainStageNames [private]

m_msTimeDomainStageNames holds the names of the time stages.

Definition at line 3008 of file OSInstance.h.

int * OSInstance::m_miTimeDomainStageVariableNumber [private]

m_miTimeDomainStageVariableNumber holds the number of variables in each stage.

Definition at line 3016 of file OSInstance.h.

int ** OSInstance::m_mmiTimeDomainStageVarList [private]

m_mmiTimeDomainStageVarList holds the list of variables in each stage.

Definition at line 3021 of file OSInstance.h.

int * OSInstance::m_miTimeDomainStageConstraintNumber [private]

m_miTimeDomainStageConstraintNumber holds the number of constraints in each stage.

Definition at line 3026 of file OSInstance.h.

int ** OSInstance::m_mmiTimeDomainStageConList [private]

m_mmiTimeDomainStageConList holds the list of constraints in each stage.

Definition at line 3031 of file OSInstance.h.

int * OSInstance::m_miTimeDomainStageObjectiveNumber [private]

m_miTimeDomainStageObjectiveNumber holds the number of objectives in each stage.

Definition at line 3036 of file OSInstance.h.

int ** OSInstance::m_mmiTimeDomainStageObjList [private]

m_mmiTimeDomainStageObjList holds the list of objectives in each stage.

Definition at line 3041 of file OSInstance.h.

CppAD::ADFun<double>* OSInstance::Fad

F is a CppAD function the range space is the objective + constraints functions, x is the domeain space.

Definition at line 4752 of file OSInstance.h.

bool OSInstance::bUseExpTreeForFunEval

bUseExpTreeForFunEval is set to true if you wish to use the OS Expression Tree for function evaluations instead of AD -- false by default.

Definition at line 4899 of file OSInstance.h.

InstanceHeader* OSInstance::instanceHeader

A pointer to an InstanceHeader object.

Definition at line 751 of file OSInstance.h.

std::map<int, OSExpressionTree*> OSInstance::m_mapExpressionTrees [private]

m_mapExpressionTrees holds a hash map of expression tree pointers, with the key being the row index and value being the expression tree representing the nonlinear expression of that row.

Definition at line 1110 of file OSInstance.h.

OSExpressionTree* OSInstance::m_LagrangianExpTree [private]

m_LagrangianExpTree is an OSExpressionTree object that is the expression tree for the Lagrangian function.

Definition at line 1120 of file OSInstance.h.

std::map<int, OSExpressionTree*> OSInstance::m_mapExpressionTreesMod [private]

m_mapExpressionTreesMod holds a map of expression trees, with the key being the row index and value being the expression tree representing a modification of the nonlinear expression of that row.

We incorporate the linear and quadratic term for a variable into the corresponding expression tree before gradient and Hessian calculations

Definition at line 1160 of file OSInstance.h.

---

The documentation for this class was generated from the following files:

• /home/coin/svn-release/OS-2.10.0/OS/src/OSCommonInterfaces/OSInstance.h
• /home/coin/svn-release/OS-2.10.0/OS/v2.0/OSInstance.h
• /home/coin/svn-release/OS-2.10.0/OS/src/OSCommonInterfaces/OSInstance.cpp