Data Structures
class	conopt.ConstraintType

class	conopt.ObjectiveElement

class	conopt.Sense

Functions
void	conopt.ModelData.setProblemDimension (long numvar, long numcons, long numnz, long numnlnz)

int	conopt.ModelData.addConstraint (ConstraintType constype, double rhs, int slackstatus)

int	conopt.ModelData.addConstraint (ConstraintType constype, double rhs)

int	conopt.ModelData.addConstraint (ConstraintType constype, double rhs, int[] varindex, double[] value, int[] nlflag, int slackstatus)

int	conopt.ModelData.addConstraint (ConstraintType constype, double rhs, int[] varindex, double[] value, int[] nlflag)

int	conopt.ModelData.addVariable (double lower, double upper, double curr, int varstatus)

int	conopt.ModelData.addVariable (double lower, double upper, double curr)

int	conopt.ModelData.addVariable (double lower, double upper)

int	conopt.ModelData.addVariable (double lower, double upper, int[] consindex, double[] value, int[] nlflag, double curr, int varstatus)

int	conopt.ModelData.addVariable (double lower, double upper, int[] consindex, double[] value, int[] nlflag, double curr)

int	conopt.ModelData.addVariable (double lower, double upper, int[] consindex, double[] value, int[] nlflag)

void	conopt.ModelData.setObjectiveElement (ObjectiveElement elem, int elemindex)

void	conopt.ModelData.setOptimizationSense (Sense sense)

void	conopt.ModelData.setInitialStatusOption (int inistat)

Detailed Description

Methods that are used to define the model to be solved by CONOPT.

The model is defined by iteratively adding variables and constraints using the conopt.ModeData.addConstraint and conopt.ModeData.addVariable methods.

Function Documentation

◆ setProblemDimension()

void conopt.ModelData.setProblemDimension	(	long	numvar,
		long	numcons,
		long	numnz,
		long	numnlnz )

inline

sets the problem dimension. This is called if the user wants to implement a custom readMatrix() method.

NOTE: it is not possible to call setProblemDimension() and addConstraint() or addVariable(). The latter functions can only be used if the problem dimension is not set and the default readMatrix() method is used.

Parameters

numvar	the number of variables in the problem
numcons	the number of constraints in the problem
numnz	the number of non-zeros in the constraint matrix
numnlnz	the number of nonlinear non-zeros in the constraint matrix

Reimplemented from conopt.ConoptModelData.

Definition at line 276 of file ModelData.java.

◆ addConstraint() [1/4]

int conopt.ModelData.addConstraint	(	ConstraintType	constype,
		double	rhs,
		int	slackstatus )

inline

adds a constraint to the problem. The non-zero coefficients are added later

Parameters

constype	the type of constraint, 0: ==, 1: >=, 2: <=, 3: free
rhs	the right hand side
slackstatus	initial status of the slack variables, see IniStat

Reimplemented from conopt.ConoptModelData.

Definition at line 290 of file ModelData.java.

◆ addConstraint() [2/4]

int conopt.ModelData.addConstraint	(	ConstraintType	constype,
		double	rhs )

inline

adds a constraint to the problem. The non-zero coefficients are added later

Parameters

constype	the type of constraint, 0: ==, 1: >=, 2: <=, 3: free
rhs	the right hand side

Reimplemented from conopt.ConoptModelData.

Definition at line 304 of file ModelData.java.

◆ addConstraint() [3/4]

int conopt.ModelData.addConstraint	(	ConstraintType	constype,
		double	rhs,
		int[]	varindex,
		double[]	value,
		int[]	nlflag,
		int	slackstatus )

inline

adds a constraint to the problem. The matrix non-zeros are added based on the supplied variables

Parameters

constype	the type of constraint, 0: ==, 1: >=, 2: <=, 3: free
rhs	the right hand side
varindex	the variables this constraint has non-zero coefficients
value	the non-zero of the variable
nlflag	flag to set whether the variable belongs to a non-linear term
slackstatus	initial status of the slack variables, see IniStat

Reimplemented from conopt.ConoptModelData.

Definition at line 321 of file ModelData.java.

◆ addConstraint() [4/4]

int conopt.ModelData.addConstraint	(	ConstraintType	constype,
		double	rhs,
		int[]	varindex,
		double[]	value,
		int[]	nlflag )

inline

adds a constraint to the problem. The matrix non-zeros are added based on the supplied variables

Parameters

constype	the type of constraint, 0: ==, 1: >=, 2: <=, 3: free
rhs	the right hand side
varindex	the variables this constraint has non-zero coefficients
value	the non-zero of the variable
nlflag	flag to set whether the variable belongs to a non-linear term

Reimplemented from conopt.ConoptModelData.

Definition at line 338 of file ModelData.java.

◆ addVariable() [1/6]

int conopt.ModelData.addVariable	(	double	lower,
		double	upper,
		double	curr,
		int	varstatus )

inline

adds a variable to the model. The non-zero coefficients are added later.

Parameters

lower	lower bound for the variable
upper	upper bound for the variable
curr	initial value of the variable, can be set to 0
varstatus	initial status of the variable, see IniStat

Reimplemented from conopt.ConoptModelData.

Definition at line 353 of file ModelData.java.

◆ addVariable() [2/6]

int conopt.ModelData.addVariable	(	double	lower,
		double	upper,
		double	curr )

inline

adds a variable to the model. The non-zero coefficients are added later.

Parameters

lower	lower bound for the variable
upper	upper bound for the variable
curr	initial value of the variable, can be set to 0

Reimplemented from conopt.ConoptModelData.

Definition at line 368 of file ModelData.java.

◆ addVariable() [3/6]

int conopt.ModelData.addVariable	(	double	lower,
		double	upper )

inline

adds a variable to the model. The non-zero coefficients are added later.

Parameters

lower	lower bound for the variable
upper	upper bound for the variable

Reimplemented from conopt.ConoptModelData.

Definition at line 382 of file ModelData.java.

◆ addVariable() [4/6]

int conopt.ModelData.addVariable	(	double	lower,
		double	upper,
		int[]	consindex,
		double[]	value,
		int[]	nlflag,
		double	curr,
		int	varstatus )

inline

adds a variable to the problem. The matrix non-zeros are added based on the supplied constraints.

Parameters

lower	lower bound for the variable
upper	upper bound for the variable
consindex	the constraints this variable has non-zero coefficients
value	the non-zero of the variable
nlflag	flag to set whether the variable belongs to a non-linear term
curr	initial value of the variable, can be set to 0
varstatus	initial status of the variable, see IniStat

Reimplemented from conopt.ConoptModelData.

Definition at line 400 of file ModelData.java.

◆ addVariable() [5/6]

int conopt.ModelData.addVariable	(	double	lower,
		double	upper,
		int[]	consindex,
		double[]	value,
		int[]	nlflag,
		double	curr )

inline

adds a variable to the problem. The matrix non-zeros are added based on the supplied constraints.

Parameters

lower	lower bound for the variable
upper	upper bound for the variable
consindex	the constraints this variable has non-zero coefficients
value	the non-zero of the variable
nlflag	flag to set whether the variable belongs to a non-linear term
curr	initial value of the variable, can be set to 0

Reimplemented from conopt.ConoptModelData.

Definition at line 418 of file ModelData.java.

◆ addVariable() [6/6]

int conopt.ModelData.addVariable	(	double	lower,
		double	upper,
		int[]	consindex,
		double[]	value,
		int[]	nlflag )

inline

adds a variable to the problem. The matrix non-zeros are added based on the supplied constraints.

Parameters

lower	lower bound for the variable
upper	upper bound for the variable
consindex	the constraints this variable has non-zero coefficients
value	the non-zero of the variable
nlflag	flag to set whether the variable belongs to a non-linear term

Reimplemented from conopt.ConoptModelData.

Definition at line 435 of file ModelData.java.

◆ setObjectiveElement()

void conopt.ModelData.setObjectiveElement	(	ObjectiveElement	elem,
		int	elemindex )

inline

sets the index for the objective variable or constraint

Reimplemented from conopt.ConoptModelData.

Definition at line 445 of file ModelData.java.

◆ setOptimizationSense()

void conopt.ModelData.setOptimizationSense ( Sense sense )

inline

sets the optimisation direction.

Reimplemented from conopt.ConoptModelData.

Definition at line 455 of file ModelData.java.

◆ setInitialStatusOption()

void conopt.ModelData.setInitialStatusOption ( int inistat )

inline

the setting to indicate how the initial status of the variables and slack variables will be handled.

The initial status is set in the addVariable() and addConstraint() methods, or in the readMatrix() method if the classical model input approach is used. By default, the value of inistat is 0, which means that the variable and slack status is ignored.

If inistat == 1: The variable status has the following behaviour:

0: The variable is initialized non-basic (if curr = lower or curr = upper) or super-basic, and
1: The variable is initialized basic The slack status has the following behaviour:
0: The slack is initialized non-basic (if the constraint is binding in the initial point) or super-basic,
1: The slack is initialized basic

If inistat == 2: The variable status has the following behaviour:

0: The variable is initialized at lower bound
1: The variable is initialized at upper bound
2: The variable is initialized basic, and
3: The variable is initialized superbasic. The slack status has the following behaviour:
0: The slack is initialized at lower bound.
1: The slack is initialized at upper bound.
2: The slack is initialized basic, and
3: The slack is initialized superbasic.

Reimplemented from conopt.ConoptModelData.

Definition at line 489 of file ModelData.java.

Data Structures

Functions

Detailed Description

Function Documentation

◆ setProblemDimension()

◆ addConstraint() [1/4]

◆ addConstraint() [2/4]

◆ addConstraint() [3/4]

◆ addConstraint() [4/4]

◆ addVariable() [1/6]

◆ addVariable() [2/6]

◆ addVariable() [3/6]

◆ addVariable() [4/6]

◆ addVariable() [5/6]

◆ addVariable() [6/6]

◆ setObjectiveElement()

◆ setOptimizationSense()

◆ setInitialStatusOption()