OptimizationModel Constructor

protected OptimizationModel(
	Func<string, DecisionVariable> variableConstructor
)

Protected Sub New ( 
	variableConstructor As Func(Of String, DecisionVariable)
)

protected:
OptimizationModel(
	Func<String^, DecisionVariable^>^ variableConstructor
)

new : 
        variableConstructor : Func<string, DecisionVariable> -> OptimizationModel

Parameters

variableConstructor  Func<String, DecisionVariable>

 

protected OptimizationModel(
	Func<string, DecisionVariable> variableConstructor,
	Matrix<double> constraints,
	Vector<double> rightHandSides
)

Protected Sub New ( 
	variableConstructor As Func(Of String, DecisionVariable),
	constraints As Matrix(Of Double),
	rightHandSides As Vector(Of Double)
)

protected:
OptimizationModel(
	Func<String^, DecisionVariable^>^ variableConstructor, 
	Matrix<double>^ constraints, 
	Vector<double>^ rightHandSides
)

new : 
        variableConstructor : Func<string, DecisionVariable> * 
        constraints : Matrix<float> * 
        rightHandSides : Vector<float> -> OptimizationModel

Parameters

variableConstructor  Func<String, DecisionVariable>

A function that creates a decision variable from a specified name.

constraints  Matrix<Double>

The matrix of coefficients of the constraints.

rightHandSides  Vector<Double>

The vector of right-hand-sides of the constraints.

Use this constructor to create a linear program in standard form. 'Standard form' means that all constraints are inequality constraints with an upper bound, and that all variables are positive.

Even though it is possible to transform every linear program into standard form, it is usually much more efficient to encode the constraints in a more compact form using one of the other constructors.

The variables are given the names x1, x2... Constraints are given the names C1, C2...

protected OptimizationModel(
	Func<string, DecisionVariable> variableConstructor,
	Matrix<double> constraints,
	Vector<double> rightHandSides,
	int equalities
)

Protected Sub New ( 
	variableConstructor As Func(Of String, DecisionVariable),
	constraints As Matrix(Of Double),
	rightHandSides As Vector(Of Double),
	equalities As Integer
)

protected:
OptimizationModel(
	Func<String^, DecisionVariable^>^ variableConstructor, 
	Matrix<double>^ constraints, 
	Vector<double>^ rightHandSides, 
	int equalities
)

new : 
        variableConstructor : Func<string, DecisionVariable> * 
        constraints : Matrix<float> * 
        rightHandSides : Vector<float> * 
        equalities : int -> OptimizationModel

Parameters

variableConstructor  Func<String, DecisionVariable>

A function that creates a decision variable from a specified name.

constraints  Matrix<Double>

The matrix of coefficients of the constraints.

rightHandSides  Vector<Double>

The vector of right-hand-sides of the constraints.

equalities  Int32

The number of equality constraints.

Use this constructor to create a linear program in standard form with equality constraints. It is more efficient to specify an equality constraint as a single constraint rather than as two inequality constraints with opposite bounds. This constructor is preferred for linear programs in standard form with equality constraints. The equalities must be listed first in the constraint matrix and in the right-hand sides, followed by the inequalities.

Note that it is much more efficient to specify bounds on variables directly than to encode the bounds in additional constraints. It is also more efficient to specify a boxed constraint as a single constraint than as two inequality constraints with opposite bounds. For linear programs with such constraints, the more general constructor is recommended.

The variables are given the names x1, x2... Constraints are given the names C1, C2...

protected OptimizationModel(
	Func<string, DecisionVariable> variableConstructor,
	Matrix<double> constraints,
	Vector<double> constraintLowerBounds,
	Vector<double> constraintUpperBounds,
	Vector<double> variableLowerBounds,
	Vector<double> variableUpperBounds
)

Protected Sub New ( 
	variableConstructor As Func(Of String, DecisionVariable),
	constraints As Matrix(Of Double),
	constraintLowerBounds As Vector(Of Double),
	constraintUpperBounds As Vector(Of Double),
	variableLowerBounds As Vector(Of Double),
	variableUpperBounds As Vector(Of Double)
)

protected:
OptimizationModel(
	Func<String^, DecisionVariable^>^ variableConstructor, 
	Matrix<double>^ constraints, 
	Vector<double>^ constraintLowerBounds, 
	Vector<double>^ constraintUpperBounds, 
	Vector<double>^ variableLowerBounds, 
	Vector<double>^ variableUpperBounds
)

new : 
        variableConstructor : Func<string, DecisionVariable> * 
        constraints : Matrix<float> * 
        constraintLowerBounds : Vector<float> * 
        constraintUpperBounds : Vector<float> * 
        variableLowerBounds : Vector<float> * 
        variableUpperBounds : Vector<float> -> OptimizationModel

Parameters

variableConstructor  Func<String, DecisionVariable>

A function that creates a decision variable from a specified name.

constraints  Matrix<Double>

The matrix of coefficients of the constraints.

constraintLowerBounds  Vector<Double>

The vector of lower bounds for the constraints.

constraintUpperBounds  Vector<Double>

The vector of upper bounds for the constraints. Must not be null.

variableLowerBounds  Vector<Double>

The vector of lower bounds for the variables.

variableUpperBounds  Vector<Double>

The vector of upper bounds for the variables.

Use this constructor to create a linear program with the most general definition. Any type of constraint can be specified, including a boxed constraint with both a lower and an upper bound. Where by default, variables are restricted to be positive, this constructor allows arbitrary bounds to be set for variables.

Note that it is much more efficient to specify bounds on variables than to encode the bounds in additional constraints. It is also more efficient to specify a boxed or equality constraint as a single constraint than as two inequality constraints with opposite bounds.

The variables are given the names x1, x2... Constraints are given the names C1, C2...

Reference