PopulationBasedOptimizer<TSolution, TPopulation, TCandidate> Class

Represents an optimizer that uses a population-based algorithm.

Definition

Namespace: Numerics.NET.Optimization
Assembly: Numerics.NET (in Numerics.NET.dll) Version: 9.1.0

public abstract class PopulationBasedOptimizer<TSolution, TPopulation, TCandidate> : MultidimensionalOptimizer<TSolution, OptimizationSolutionReport<TSolution>>
where TPopulation : Population<TSolution, TCandidate>
where TCandidate : Object, ICandidate<TSolution>

Visual Basic

Public MustInherit Class PopulationBasedOptimizer(Of TSolution, TPopulation As Population(Of TSolution, TCandidate), TCandidate As {Object, ICandidate(Of TSolution)})
	Inherits MultidimensionalOptimizer(Of TSolution, OptimizationSolutionReport(Of TSolution))

C++/CLI

generic<typename TSolution, typename TPopulation, typename TCandidate>
where TPopulation : Population<TSolution, TCandidate>
where TCandidate : Object, ICandidate<TSolution>
public ref class PopulationBasedOptimizer abstract : public MultidimensionalOptimizer<TSolution, OptimizationSolutionReport<TSolution>^>

[<AbstractClassAttribute>]
type PopulationBasedOptimizer<'TSolution, 'TPopulation, 'TCandidate when 'TPopulation : Population<'TSolution, 'TCandidate> when 'TCandidate : Object and ICandidate<'TSolution>> = 
    class
        inherit MultidimensionalOptimizer<'TSolution, OptimizationSolutionReport<'TSolution>>
    end

Inheritance: Object → ManagedIterativeAlgorithm<TSolution, Double, OptimizationSolutionReport<TSolution>> → MultidimensionalOptimizer<TSolution, OptimizationSolutionReport<TSolution>> → PopulationBasedOptimizer<TSolution, TPopulation, TCandidate>

Derived: Numerics.NET.Optimization.PopulationBasedOptimizer<TPopulation, TCandidate>

Type Parameters

TSolution: The type of the solutions.
TPopulation: The type of the population. Must inherit from Population<TSolution, TCandidate>
TCandidate: The type of the candidate solutions that make up the population. Must implement ICandidate<TSolution>.

Constructors

PopulationBasedOptimizer<TSolution, TPopulation, TCandidate>

Constructs a new [!:PopulationBasedOptimizer] class.

Properties

ConvergenceTests	Gets the collection of convergence tests for the algorithm. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
DiversityTest	Gets the convergence test that measures population diversity.
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. (Inherited from MultidimensionalOptimizer<T, TReport>)
ExtremumType	Gets or sets the type of extremum. (Inherited from MultidimensionalOptimizer<T, TReport>)
HasConstraints	Gets a value indicating whether the optimizer has constraints.
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. (Inherited from MultidimensionalOptimizer<T, TReport>)
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>)
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. (Inherited from MultidimensionalOptimizer<T, TReport>)
ParallelOptions	Gets or sets the configuration for the parallel behavior of the algorithm. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
Population	Gets the current population of solutions.
PopulationConvergenceTest	Gets the convergence test that uses the population's coefficient of variation.
PopulationSize	Gets or sets the population size used in the algorithm.
Random	Gets or sets the random number generator used by the optimizer.
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>)
Status	Gets the AlgorithmStatus following an execution of the algorithm. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
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. (Inherited from MultidimensionalOptimizer<T, TReport>)
Values	Gets the function values of the current population.
ValueTest	Gets the SimpleConvergenceTest<T> that uses the value of the target functions. (Inherited from MultidimensionalOptimizer<T, TReport>)

Methods

AddConstraint	Adds a constraint function g(x) that must satisfy g(x) ≤ 0.
ClearConstraints	Clears all constraint functions.
Equals	Determines whether the specified object is equal to the current object. (Inherited from Object)
Evaluate	Evaluates the objective function. (Inherited from MultidimensionalOptimizer<T, TReport>)
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. (Inherited from MultidimensionalOptimizer<T, TReport>)
FindMaximum	Searches for a maximum. (Inherited from MultidimensionalOptimizer<T, TReport>)
FindMinimum	Searches for a minimum. (Inherited from MultidimensionalOptimizer<T, TReport>)
GetConstraintViolation	Gets the total constraint violation for a given solution vector.
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. (Inherited from MultidimensionalOptimizer<T, TReport>)
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. (Inherited from MultidimensionalOptimizer<T, TReport>)
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. (Inherited from MultidimensionalOptimizer<T, TReport>)
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)