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IActiveSetQPSolver Class

Class IActiveSetQPSolver is an interface for classes that solver convex quadratic programming (QP) problems. In particular, classes that implement this abstract class may be used in the Active Set Sequential Quadratic Programming solver for general linear programming problems.
Inheritance Hierarchy

Namespace:  CenterSpace.NMath.Core
Assembly:  NMath (in NMath.dll) Version: 7.3
Syntax
public abstract class IActiveSetQPSolver

The IActiveSetQPSolver type exposes the following members.

Constructors
  NameDescription
Protected methodIActiveSetQPSolver
Initializes a new instance of the IActiveSetQPSolver class
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Properties
  NameDescription
Public propertyActiveSet
Gets the set of active constraint Indices for the solution. If algorithm did not converge it returns these Indices for the final iteration.
Public propertyIterations
The number of iterations performed before the algorithm terminated.
Public propertyLagrangeMultiplier
Gets the values of the Lagrange multipliers for the solution if the algorithm converged. If it did not converge it returns the values of the Lagrange multiplier for the final iteration.
Public propertyMaxIterations
Gets and sets the maximum number of iterations to perform.
Public propertyMaxSeconds
Gets and sets the maximum number of seconds to spend in the inequality constrained QP solver.
Public propertyOptimalObjectiveFunctionValue
If the solver was successful, OptimalObjectiveFunctionValue returns the minimum value of the objective function.
Public propertyOptimalX
If the solver was successful, OptimalX returns the point at which the objective function is minimized.
Public propertyStatus
Gets the status of the solver for the most recent solution attempt.
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Methods
  NameDescription
Public methodSolve(QuadraticProgrammingProblem)
Solves the given convex quadratic programming problem.
Public methodSolve(QuadraticProgrammingProblem, DoubleVector)
Solves the given convex quadratic programming problem.
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Remarks
QP problems are of the form:
Minimize 0.5*x'Hx + x'c

Subject to
ai'x = bi, for i in E,
ai'x >= bi, for i in I

where H is a symmetric matrix (sometimes called the Hessian) and E and I are finite sets of Indices, using an active-set method. This method is applicable only to convex problems, in which the matrix H is positive semidefinite.
See Also