A B C D E F G I L M N P R S T V W

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set(int, Individual) - Method in class DistributedEvolutionaryAlgorithmsFramework.Population

Sets one Individual with index j, rewriting the old one

setEmigrationMethod(Population.expelEmigrantsMethod) - Method in class DistributedEvolutionaryAlgorithmsFramework.Deaf

Determines how emigrating individuals are chosen.

setEmigrationMethod(Population.expelEmigrantsMethod) - Method in class DistributedEvolutionaryAlgorithmsFramework.Framework

Determines how emigrating individuals are chosen.

setFitness(double) - Method in class DistributedEvolutionaryAlgorithmsFramework.Individual

Sets Individuals fitness to given value f

setFitnessFunction(FitnessFunction) - Method in class DistributedEvolutionaryAlgorithmsFramework.Population

Sets fitness function of this Population which is later used to create Individuals and determine their fitness

setGene(int, double) - Method in class DistributedEvolutionaryAlgorithmsFramework.Individual

Sets one gene to defined value val

setHistoryPath(String) - Method in class DistributedEvolutionaryAlgorithmsFramework.Deaf

setHistoryPath(String) - Method in class DistributedEvolutionaryAlgorithmsFramework.Framework

setImmigrationMethod(Population.acceptImmigrantsMethod) - Method in class DistributedEvolutionaryAlgorithmsFramework.Deaf

Determines how immigrating individuals are handled.

setImmigrationMethod(Population.acceptImmigrantsMethod) - Method in class DistributedEvolutionaryAlgorithmsFramework.Framework

Determines how immigrating individuals are handled.

setIndex(int) - Method in class DistributedEvolutionaryAlgorithmsFramework.Individual

Sets population index to value i

setKey(int) - Method in class DistributedEvolutionaryAlgorithmsFramework.Population

Each population has its unique key given by the framework at initialization by this function.

setMapTasks(int) - Method in class DistributedEvolutionaryAlgorithmsFramework.Deaf

Setting for hadoop.

setMapTasks(int) - Method in class DistributedEvolutionaryAlgorithmsFramework.Framework

Setting for hadoop.

setMaxRestriction(double[]) - Method in class DistributedEvolutionaryAlgorithmsFramework.FitnessFunction

Set maximal constraints for each dimension of specimen

setMigratingFlag() - Method in class DistributedEvolutionaryAlgorithmsFramework.Population

Migrating flag marks if the population is used for evolution or for migration

setMinRestriction(double[]) - Method in class DistributedEvolutionaryAlgorithmsFramework.FitnessFunction

Set minimal constraints for each dimension of specimen

setParameter(String, float) - Method in class DistributedEvolutionaryAlgorithmsFramework.Algorithm

Sets externally defined algorithm specific parameters.

setPopulation(Population) - Method in class DistributedEvolutionaryAlgorithmsFramework.Algorithm

Sets main population to given Population

setPopulation(Population) - Method in class DistributedEvolutionaryAlgorithmsFramework.Individual

Sets population pointer to pop

setPopulation(ArrayList<Individual>) - Method in class DistributedEvolutionaryAlgorithmsFramework.Population

Makes new Population from Individuals given in the individuals parameter

setRepeatedTest(boolean) - Method in class DistributedEvolutionaryAlgorithmsFramework.Deaf

setRepeatedTest(boolean) - Method in class DistributedEvolutionaryAlgorithmsFramework.Framework

setTopology(Class<? extends Topology>) - Method in class DistributedEvolutionaryAlgorithmsFramework.Deaf

setTopology(Class<? extends Topology>) - Method in class DistributedEvolutionaryAlgorithmsFramework.Framework

setValue(int, double) - Method in class DistributedEvolutionaryAlgorithmsFramework.Individual

Sets value of one gene

setValues(double[]) - Method in class DistributedEvolutionaryAlgorithmsFramework.Individual

Sets whole genotype

setVerbose(boolean) - Method in class DistributedEvolutionaryAlgorithmsFramework.Deaf

If verbose setting is set to true, all populations with all their individuals will be written to Logger

setVerbose(boolean) - Method in class DistributedEvolutionaryAlgorithmsFramework.Framework

If verbose setting is set to true, all populations with all their individuals will be written to Logger

setWriteHistory(boolean) - Method in class DistributedEvolutionaryAlgorithmsFramework.Deaf

setWriteHistory(boolean) - Method in class DistributedEvolutionaryAlgorithmsFramework.Framework

size() - Method in class DistributedEvolutionaryAlgorithmsFramework.Population

sort() - Method in class DistributedEvolutionaryAlgorithmsFramework.Population

Sorts the population by fitness

specimenLength - Variable in class DistributedEvolutionaryAlgorithmsFramework.FitnessFunction

Length of genotype / number of dimensions.