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GeneticAlgorithmT Class

Algorithm logic class
Inheritance Hierarchy
SystemObject
  FinMath.MachineLearning.EvolutionaryAlgorithmsGeneticAlgorithmT

Namespace:  FinMath.MachineLearning.EvolutionaryAlgorithms
Assembly:  FinMath (in FinMath.dll) Version: 2.4.7-0a995bd0ea1854c2c868ec3f8dae606c5777e170
Syntax
C#
public class GeneticAlgorithm<T>

Type Parameters

T
Individual's type.

The GeneticAlgorithmT type exposes the following members.

Constructors
  NameDescription
Public methodGeneticAlgorithmT(GeneticAlgorithmTCreationDelegateType, GeneticAlgorithmTCrossoverOneChildDelegateType, GeneticAlgorithmTMutationDelegateType, GeneticAlgorithmTObjectiveBlockDelegateType)
Constructor
Public methodGeneticAlgorithmT(GeneticAlgorithmTCreationDelegateType, GeneticAlgorithmTCrossoverOneChildDelegateType, GeneticAlgorithmTMutationDelegateType, GeneticAlgorithmTObjectiveDelegateType)
Constructor
Public methodGeneticAlgorithmT(GeneticAlgorithmTCreationDelegateType, GeneticAlgorithmTCrossoverTwoChildrenDelegateType, GeneticAlgorithmTMutationDelegateType, GeneticAlgorithmTObjectiveBlockDelegateType)
Constructor
Public methodGeneticAlgorithmT(GeneticAlgorithmTCreationDelegateType, GeneticAlgorithmTCrossoverTwoChildrenDelegateType, GeneticAlgorithmTMutationDelegateType, GeneticAlgorithmTObjectiveDelegateType)
Constructor
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Properties
  NameDescription
Public propertyBestIndividual
The best individual from current population.
Public propertyBestObjective
Objective of the best individual from current population.
Public propertyCreationDelegate
Creation a new individual delegate.
Public propertyCrossoverOneChildDelegate
Crossovers two individuals and produces one child delegate.
Public propertyCrossoverTwoChildrenDelegate
Crossovers two individuals and produces one child delegate.
Public propertyDominationPercent Obsolete.
Percent of population that will be left intact.
Public propertyDominationRate
The part of population that will be left intact [0,1].
Public propertyEliteDelegate
Elite determination delegate.
Public propertyEliteSize
Size of elite of current generation.
Public propertyElitismPercent Obsolete.
Percent of population selected for crossover [0,100].
Public propertyElitismRate
The part of population selected for crossover [0,1].
Public propertyExitDelegate
Exit condition determination delegate.
Public propertyFitnessScaling
Fitness scaling type
Public propertyGeneration
Current generation number.
Public propertyGenerationsCount
Number of generations algorithm will made
Public propertyMutationDelegate
Mutates individual delegate.
Public propertyMutationPercent Obsolete.
Percent of next population that will be mutated [0,100].
Public propertyMutationRate
The part of next population that will be mutated [0,1].
Public propertyObjectInitializationDelegate
The new empty object creation delegate.
Public propertyObjectiveDelegate
Objective estimation delegate. Minimal value is searched.
Public propertyObjectiveValues
The objective values array.
Public propertyPopulation
Current population.
Public propertyPopulationSize
Population size of each generation.
Public propertyRandom
Random generator.
Public propertySelectionAlgorithm
Selection algorithm.
Public propertySelectionFunction
Selection probability function type
Public propertyTournamentSize
Tournament size for tournament selection.
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Methods
  NameDescription
Public methodContinue
Continue algorithm execution from the place it has stopped.
Public methodEquals
Determines whether the specified object is equal to the current object.
(Inherited from Object.)
Public methodGetHashCode
Serves as the default hash function.
(Inherited from Object.)
Public methodGetType
Gets the Type of the current instance.
(Inherited from Object.)
Public methodRun
Starts algorithms.
Public methodStop
Stops algorithm
Public methodToString
Returns a string that represents the current object.
(Inherited from Object.)
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See Also