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LinearProgrammingProblem Class

Class LinearProgrammingProblem encapsulates a Linear programming problem.
Inheritance Hierarchy

Namespace:  CenterSpace.NMath.Core
Assembly:  NMath (in NMath.dll) Version: 7.3
Syntax
[SerializableAttribute]
public class LinearProgrammingProblem : LinearConstrainedProblem, 
	ICloneable

The LinearProgrammingProblem type exposes the following members.

Constructors
  NameDescription
Public methodLinearProgrammingProblem
Default constructor. Behavior of resulting object is undefined.
Public methodLinearProgrammingProblem(DoubleVector)
Constructs a LinearProgrammingProblem object for minimizing objective function dot(objectiveCoefficients, x), where x is the vector of variables.
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Properties
  NameDescription
Public propertyConstraints
Gets and sets the linear constraints for the problem.
(Inherited from LinearConstrainedProblem.)
Public propertyNumVariables
Gets the number of variables.
(Overrides BoundedVariableProblemNumVariables.)
Public propertyObjectiveCoefficients
Gets and sets the coefficients for the objective function.
Public propertyVariableBounds
Gets and sets variable bounds for the problem.
(Inherited from BoundedVariableProblem.)
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Methods
  NameDescription
Public methodAddBounds(Int32, Double, Double)
Adds upper and lower bound constraints to a variable.
(Inherited from BoundedVariableProblem.)
Public methodAddBounds(Int32, Double, Double, Double)
Adds upper and lower bound constraints to a variable.
(Inherited from BoundedVariableProblem.)
Public methodAddConstraint(LinearConstraint)
Adds the given constraint to the problem.
(Inherited from LinearConstrainedProblem.)
Public methodAddConstraint(DoubleVector, Double, Double)
Adds a linear inequality constraint of the form lowerBound <= coefficients'x < upperBound
(Inherited from LinearConstrainedProblem.)
Public methodAddConstraint(ILinearConstraintCoefficients, Double, Double)
Adds a linear inequality constraint of the form lowerBound <= coefficients'x < upperBound
(Inherited from LinearConstrainedProblem.)
Public methodAddConstraint(DoubleVector, Double, Double, Double)
Adds a linear inequality constraint of the form lowerBound <= coefficients'x < upperBound
(Inherited from LinearConstrainedProblem.)
Public methodAddConstraint(ILinearConstraintCoefficients, Double, Double, Double)
Adds a linear inequality constraint of the form lowerBound <= coefficients'x < upperBound
(Inherited from LinearConstrainedProblem.)
Public methodAddEqualityConstraint(DoubleVector, Double)
Adds an equality constraint of the form coefficients'x = rightHandSide
(Inherited from LinearConstrainedProblem.)
Public methodAddEqualityConstraint(ILinearConstraintCoefficients, Double)
Adds an equality constraint of the form coefficients'x = rightHandSide
(Inherited from LinearConstrainedProblem.)
Public methodAddLowerBound(Int32, Double)
Adds an lower bound constraint on the variable at the given index.
(Inherited from BoundedVariableProblem.)
Public methodAddLowerBound(Int32, Double, Double)
Adds an lower bound constraint on the variable at the given index.
(Inherited from BoundedVariableProblem.)
Public methodAddLowerBoundConstraint(DoubleVector, Double)
Adds a linear inequality constraint of the form coefficients'x >= lowerBound
(Inherited from LinearConstrainedProblem.)
Public methodAddLowerBoundConstraint(ILinearConstraintCoefficients, Double)
Adds a linear inequality constraint of the form coefficients'x >= lowerBound
(Inherited from LinearConstrainedProblem.)
Public methodAddLowerBoundConstraint(DoubleVector, Double, Double)
Adds a linear inequality constraint of the form coefficients'x >= lowerBound
(Inherited from LinearConstrainedProblem.)
Public methodAddLowerBoundConstraint(ILinearConstraintCoefficients, Double, Double)
Adds a linear inequality constraint of the form coefficients'x >= lowerBound
(Inherited from LinearConstrainedProblem.)
Public methodAddUpperBound(Int32, Double)
Adds an upper bound constraint on the variable at the given index.
(Inherited from BoundedVariableProblem.)
Public methodAddUpperBound(Int32, Double, Double)
Adds an upper bound constraint on the variable at the given index.
(Inherited from BoundedVariableProblem.)
Public methodAddUpperBoundConstraint(DoubleVector, Double)
Adds a linear inequality constraint of the form coefficients'x <= upperBound
(Inherited from LinearConstrainedProblem.)
Public methodAddUpperBoundConstraint(ILinearConstraintCoefficients, Double)
Adds a linear inequality constraint of the form coefficients'x <= upperBound
(Inherited from LinearConstrainedProblem.)
Public methodAddUpperBoundConstraint(DoubleVector, Double, Double)
Adds a linear inequality constraint of the form coefficients'x <= upperBound
(Inherited from LinearConstrainedProblem.)
Public methodAddUpperBoundConstraint(ILinearConstraintCoefficients, Double, Double)
Adds a linear inequality constraint of the form coefficients'x <= upperBound
(Inherited from LinearConstrainedProblem.)
Protected methodCheckVariableIndex
Checks that the given variable array index is valid.
(Overrides BoundedVariableProblemCheckVariableIndex(Int32).)
Public methodClone
Returns a deep copy of self.
Public methodEvaluateConstraints
Evaluates each of the constraints at the specified point and returns the results.
(Inherited from LinearConstrainedProblem.)
Public methodPointIsFeasible(DoubleVector)
Function for determining the feasibility of a give point. A point x is feasible if it satisfies all the constraints of the problem.
(Inherited from LinearConstrainedProblem.)
Public methodPointIsFeasible(DoubleVector, Double)
Function for determining the feasibility of a give point.
(Inherited from LinearConstrainedProblem.)
Public methodToString
Creates a string representation of the problem.
(Overrides ObjectToString.)
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Fields
  NameDescription
Protected fieldconstraints_
Problem constraints.
(Inherited from LinearConstrainedProblem.)
Protected fieldvariableBounds_
Map containing variable bounds. Key is the variable ID, the value is the bounds.
(Inherited from BoundedVariableProblem.)
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Remarks
A linear programming (LP) problem optimizes a linear objective function subject to a set of linear constraints, and optionally subject to a set of variable bounds. The simplex method solves LP problems by constructing a solution at a vertex of a simplex, then walking along edges of the simplex to vertices with successively optimal values of the objective function until the optimum is reached. For example:
See Also