MultidimensionalOptimizer Class

Represents an algorithm for optimization of a multivariate function.

Definition

Namespace: Numerics.NET.Optimization
Assembly: Numerics.NET (in Numerics.NET.dll) Version: 9.0.2
C#
public abstract class MultidimensionalOptimizer : ManagedIterativeAlgorithm<Vector<double>, double, OptimizationSolutionReport>
Inheritance
Object  →  ManagedIterativeAlgorithm<Vector<Double>, Double, OptimizationSolutionReport>  →  MultidimensionalOptimizer
Derived

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.

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>)
MaxIterationsGets 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 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

EqualsDetermines 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.
FinalizeAllows 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.
GetHashCodeServes as the default hash function.
(Inherited from Object)
GetTypeGets 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>)
MemberwiseCloneCreates 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>)
ToStringReturns a string that represents the current object.
(Inherited from Object)

See Also