MultidimensionalOptimizer Class

Represents an algorithm for optimization of a multivariate function.

Definition

Namespace: Extreme.Mathematics.Optimization
Assembly: Extreme.Numerics (in Extreme.Numerics.dll) Version: 8.1.23

public abstract class MultidimensionalOptimizer : ManagedIterativeAlgorithm<Vector<double>, double, OptimizationSolutionReport>

Visual Basic

Public MustInherit Class MultidimensionalOptimizer
	Inherits ManagedIterativeAlgorithm(Of Vector(Of Double), Double, OptimizationSolutionReport)

C++/CLI

public ref class MultidimensionalOptimizer abstract : public ManagedIterativeAlgorithm<Vector<double>^, double, OptimizationSolutionReport^>

[<AbstractClassAttribute>]
type MultidimensionalOptimizer = 
    class
        inherit ManagedIterativeAlgorithm<Vector<float>, float, OptimizationSolutionReport>
    end

Inheritance: Object → ManagedIterativeAlgorithm<Vector<Double>, Double, OptimizationSolutionReport> → MultidimensionalOptimizer

Derived: Extreme.Mathematics.Optimization.DirectionalOptimizer
Extreme.Mathematics.Optimization.NelderMeadOptimizer

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:

Class	Description
ConjugateGradientOptimizer	Represents an optimizer that uses a conjugate gradient algorithm. This class supports the Fletcher-Reeves, Polak-Ribière and positive Polak-Ribière variants.
NelderMeadOptimizer	Represents an optimizer that uses Nelder and Mead's downhill simplex algorithm.
PowellOptimizer	Represents an optimizer that uses Powell's derivative-free conjugate gradient algorithm.
QuasiNewtonOptimizer	Represents an optimizer that uses a quasi-Newton algorithm. Both the DFP (Davison-Fletcher-Powell) and BFGS (Broyden-Fletcher-Goldfard-Shanno) methods are supported.

Constructors

MultidimensionalOptimizer

Constructs a new MultidimensionalOptimizer object.

Properties

ConvergenceTests	Gets the collection of convergence tests for the algorithm. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
Dimensions	Gets or sets the number of dimensions of the optimization problem.
EstimatedError	Gets a value indicating the size of the absolute error of the result. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
EvaluationsNeeded	Gets the number of evaluations needed to execute the algorithm. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
EvaluationsRemaining	Gets the number of evaluations still available. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
Extremum	Gets or sets the current best approximation to the extremum.
ExtremumType	Gets or sets the type of extremum.
FastGradientFunction	Gets or sets the function that computes the gradient of the objective funciton.
GradientEvaluationsNeeded	Gets the number of evaluations of the gradient of the objective function.
GradientFunction	Gets or sets the function that computes the gradient of the objective funciton.
GradientTest	Gets the VectorConvergenceTest<T> that uses the gradient of the objective function.
GradientVector	Gets or sets the current value of the gradient.
HasSharedDegreeOfParallelism	Indicates whether the degree of parallelism is a property that is shared across instances. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
InitialGuess	Gets or sets the initial value for the iteration.
IterationsNeeded	Gets the number of iterations needed by the algorithm to reach the desired accuracy. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
IterationsRemaining	Gets the number of iterations remaining. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
LastCorrection	Gets the last correction to the solution of the system of equations.
MaxDegreeOfParallelism	Gets or sets the maximum degree of parallelism enabled by this instance. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
MaxEvaluations	Gets or sets the maximum number of evaluations during the calculation. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
MaxIterations	Gets or sets the maximum number of iterations to use when approximating the roots of the target function. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
MinIterations	Gets or sets the minimum iterations that have to be performed. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
ObjectiveFunction	Gets or sets the objective function.
ObjectiveFunctionWithGradient	Gets or sets a function that evaluates the value and gradient of the objective function.
ParallelOptions	Gets or sets the configuration for the parallel behavior of the algorithm. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
Result	Gets the result of an algorithm after it has executed. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
SolutionReport	Gets the result of an algorithm after it has executed. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
SolutionTest	Gets the VectorConvergenceTest<T> that uses the approximate solution.
Status	Gets the AlgorithmStatus following an execution of the algorithm. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
SymbolicObjectiveFunction	Gets or sets the objective function.
ThrowExceptionOnFailure	Gets or sets a value indicating whether to throw an exception when the algorithm fails to converge. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
ValueAtExtremum	Gets or sets the current value of the objective function.
ValueTest	Gets the SimpleConvergenceTest<T> that uses the value of the target functions.

Methods

Equals	Determines whether the specified object is equal to the current object. (Inherited from Object)
Evaluate	Evaluates the objective function.
EvaluateFunctionAndGradient	Evaluates the objective function and its gradient at the same time.
EvaluateGradient	Evaluates the gradient.
Finalize	Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection. (Inherited from Object)
FindExtremum	Searches for an extremum.
GetHashCode	Serves as the default hash function. (Inherited from Object)
GetType	Gets the Type of the current instance. (Inherited from Object)
IncrementEvaluations()	Increments the number of evaluations by one. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
IncrementEvaluations(Int32)	Increments the number of evaluations by the specified amount. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
Iterate	Performs one iteration of the algorithm. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
Iterated	Performs tasks after the iteration is completed, but before the status of the algorithm is finalized. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
MemberwiseClone	Creates a shallow copy of the current Object. (Inherited from Object)
OnConvergence	Performs any tasks after the main algorithm has converged. (Overrides ManagedIterativeAlgorithm<T, TError, TReport>.OnConvergence())
OnFailure	Performs any tasks after the main algorithm has failed to converge. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
OnInit	Performs initialization before the first iteration. (Overrides ManagedIterativeAlgorithm<T, TError, TReport>.OnInit())
ReportFailure	Records the results of an algorithm in case it fails. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
ReportResult	Records the results of an algorithm. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
ReportSuccess	Records the results of a algorithm that converged successfully. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
ResetEvaluations	Resets the number of evaluations to zero. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
Restart	Prepares the algorithm to be run again with possibly different inputs. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
Run()	Runs the algorithm. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
Run(ParallelOptions)	Runs the algorithm using the specified parallelization options. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
SetResult	Sets the results of an algorithm's execution. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
SetValueAtExtremum	Sets the value of the objective function at the extremum to the supplied value.
TestConvergence	Checks whether the algorithm has converged. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
ThreadSafeIncrementEvaluations()	Increments the number of evaluations by one. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
ThreadSafeIncrementEvaluations(Int32)	Increments the number of evaluations by the specified amount. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
ThrowConvergenceException	Interprets the AlgorithmStatus and throws the appropriate exception. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
ToString	Returns a string that represents the current object. (Inherited from Object)