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  • Extreme.Mathematics.Optimization
    • BoundedQuasiNewtonOptimizer Class
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    • MultidimensionalOptimizer Class
    • NelderMeadOptimizer Class
    • NonlinearConstraint Class
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    • OneDimensionalOptimizer Class
    • OptimizationModel Class
    • OptimizationModelEntity Class
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    • PowellOptimizer Class
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  • MultidimensionalOptimizer Class
    • MultidimensionalOptimizer Constructor
    • Properties
    • Methods

MultidimensionalOptimizer Class

Extreme Optimization Numerical Libraries for .NET Professional
Represents an algorithm for optimization of a multivariate function.
Inheritance Hierarchy

SystemObject
  Extreme.Mathematics.AlgorithmsManagedIterativeAlgorithmVectorDouble, Double, OptimizationSolutionReport
    Extreme.Mathematics.OptimizationMultidimensionalOptimizer
      Extreme.Mathematics.OptimizationDirectionalOptimizer
      Extreme.Mathematics.OptimizationNelderMeadOptimizer

Namespace:  Extreme.Mathematics.Optimization
Assembly:  Extreme.Numerics (in Extreme.Numerics.dll) Version: 8.1.1
Syntax

C#
VB
C++
F#
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public abstract class MultidimensionalOptimizer : ManagedIterativeAlgorithm<Vector<double>, double, OptimizationSolutionReport>
Public MustInherit Class MultidimensionalOptimizer
	Inherits ManagedIterativeAlgorithm(Of Vector(Of Double), Double, OptimizationSolutionReport)
public ref class MultidimensionalOptimizer abstract : public ManagedIterativeAlgorithm<Vector<double>^, double, OptimizationSolutionReport^>
[<AbstractClassAttribute>]
type MultidimensionalOptimizer =  
    class
        inherit ManagedIterativeAlgorithm<Vector<float>, float, OptimizationSolutionReport>
    end

The MultidimensionalOptimizer type exposes the following members.

Constructors

  NameDescription
Protected methodMultidimensionalOptimizer
Constructs a new MultidimensionalOptimizer object.
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Properties

  NameDescription
Public propertyConvergenceTests
Gets the collection of convergence tests for the algorithm.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.)
Public propertyDimensions
Gets or sets the number of dimensions of the optimization problem.
Public propertyEstimatedError
Gets a value indicating the size of the absolute error of the result.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.)
Public propertyEvaluationsNeeded
Gets the number of evaluations needed to execute the algorithm.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.)
Protected propertyEvaluationsRemaining
Gets the number of evaluations still available.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.)
Public propertyExtremum
Gets or sets the current best approximation to the extremum.
Public propertyExtremumType
Gets or sets the type of extremum.
Public propertyFastGradientFunction
Gets or sets the function that computes the gradient of the objective funciton.
Public propertyGradientEvaluationsNeeded
Gets the number of evaluations of the gradient of the objective function.
Public propertyGradientFunction
Gets or sets the function that computes the gradient of the objective funciton.
Public propertyGradientTest
Gets the VectorConvergenceTestT that uses the gradient of the objective function.
Public propertyGradientVector
Gets or sets the current value of the gradient.
Public propertyHasSharedDegreeOfParallelism
Indicates whether the degree of parallelism is a property that is shared across instances.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.)
Public propertyInitialGuess
Gets or sets the initial value for the iteration.
Public propertyIterationsNeeded
Gets the number of iterations needed by the algorithm to reach the desired accuracy.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.)
Protected propertyIterationsRemaining
Gets the number of iterations remaining.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.)
Protected propertyLastCorrection
Gets the last correction to the solution of the system of equations.
Public propertyMaxDegreeOfParallelism
Gets or sets the maximum degree of parallelism enabled by this instance.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.)
Public propertyMaxEvaluations
Gets or sets the maximum number of evaluations during the calculation.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.)
Public propertyMaxIterations
Gets or sets the maximum number of iterations to use when approximating the roots of the target function.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.)
Public propertyMinIterations
Gets or sets the minimum iterations that have to be performed.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.)
Public propertyObjectiveFunction
Gets or sets the objective function.
Public propertyObjectiveFunctionWithGradient
Gets or sets a function that evaluates the value and gradient of the objective function.
Public propertyParallelOptions
Gets or sets the configuration for the parallel behavior of the algorithm.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.)
Public propertyResult
Gets the result of an algorithm after it has executed.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.)
Public propertySolutionReport
Gets the result of an algorithm after it has executed.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.)
Public propertySolutionTest
Gets the VectorConvergenceTestT that uses the approximate solution.
Public propertyStatus
Gets the AlgorithmStatus following an execution of the algorithm.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.)
Public propertySymbolicObjectiveFunction
Gets or sets the objective function.
Public propertyThrowExceptionOnFailure
Gets or sets a value indicating whether to throw an exception when the algorithm fails to converge.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.)
Public propertyValueAtExtremum
Gets or sets the current value of the objective function.
Public propertyValueTest
Gets the SimpleConvergenceTestT that uses the value of the target functions.
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Methods

  NameDescription
Public methodEquals
Determines whether the specified object is equal to the current object.
(Inherited from Object.)
Protected methodEvaluate
Evaluates the objective function.
Protected methodEvaluateFunctionAndGradient
Evaluates the objective function and its gradient at the same time.
Protected methodEvaluateGradient
Evaluates the gradient.
Protected methodFinalize
Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection.
(Inherited from Object.)
Public methodFindExtremum
Searches for an extremum.
Public methodGetHashCode
Serves as the default hash function.
(Inherited from Object.)
Public methodGetType
Gets the Type of the current instance.
(Inherited from Object.)
Protected methodIncrementEvaluations
Increments the number of evaluations by one.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.)
Protected methodIncrementEvaluations(Int32)
Increments the number of evaluations by the specified amount.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.)
Protected methodIterate
Performs one iteration of the algorithm.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.)
Protected methodIterated
Performs tasks after the iteration is completed, but before the status of the algorithm is finalized.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.)
Protected methodMemberwiseClone
Creates a shallow copy of the current Object.
(Inherited from Object.)
Protected methodOnConvergence
Performs any tasks after the main algorithm has converged.
(Overrides ManagedIterativeAlgorithmT, TError, TReportOnConvergence.)
Protected methodOnFailure
Performs any tasks after the main algorithm has failed to converge.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.)
Protected methodOnInit
Performs initialization before the first iteration.
(Overrides ManagedIterativeAlgorithmT, TError, TReportOnInit.)
Protected methodReportFailure
Records the results of an algorithm in case it fails.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.)
Protected methodReportResult
Records the results of an algorithm.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.)
Protected methodReportSuccess
Records the results of a algorithm that converged successfully.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.)
Protected methodResetEvaluations
Resets the number of evaluations to zero.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.)
Protected methodRestart
Prepares the algorithm to be run again with possibly different inputs.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.)
Protected methodRun
Runs the algorithm.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.)
Protected methodRun(ParallelOptions)
Runs the algorithm using the specified parallelization options.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.)
Protected methodSetResult
Sets the results of an algorithm's execution.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.)
Protected methodSetValueAtExtremum
Sets the value of the objective function at the extremum to the supplied value.
Protected methodTestConvergence
Checks whether the algorithm has converged.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.)
Protected methodThreadSafeIncrementEvaluations
Increments the number of evaluations by one.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.)
Protected methodThreadSafeIncrementEvaluations(Int32)
Increments the number of evaluations by the specified amount.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.)
Protected methodThrowConvergenceException
Interprets the AlgorithmStatus and throws the appropriate exception.
(Inherited from ManagedIterativeAlgorithmT, TError, TReport.)
Public methodToString
Returns a string that represents the current object.
(Inherited from Object.)
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Remarks

MultidimensionalOptimizer is the abstract base class for all algorithms that implement optimization algorithms in multiple dimensions. It inherits from ManagedIterativeAlgorithm. All methods and properties of this class are available to MultidimensionalOptimizer and its derived classes.

MultidimensionalOptimizer is an abstract class and cannot be instantiated directly. Instead, use one of the following derived classes:

ClassDescription
ConjugateGradientOptimizerRepresents an optimizer that uses a conjugate gradient algorithm. This class supports the Fletcher-Reeves, Polak-Ribière and positive Polak-Ribière variants.
NelderMeadOptimizerRepresents an optimizer that uses Nelder and Mead's downhill simplex algorithm.
PowellOptimizerRepresents an optimizer that uses Powell's derivative-free conjugate gradient algorithm.
QuasiNewtonOptimizerRepresents an optimizer that uses a quasi-Newton algorithm. Both the DFP (Davison-Fletcher-Powell) and BFGS (Broyden-Fletcher-Goldfard-Shanno) methods are supported.
See Also

Reference

Extreme.Mathematics.Optimization Namespace

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