AcceptBest              Accepts only genes with equal or better
                        fitness.
AcceptFactory           Configure the acceptance function of a genetic
                        algorithm.
AcceptIVMetropolis      Individually Adaptive Metropolis Acceptance
                        Rule.
AcceptMetropolis        Metropolis Acceptance Rule.
AcceptNewGene           Accepts a new gene.
ApplyFactory            Configure the the execution model for gene
                        evaluation.
ConstCRate              Constant crossover rate.
ConstMRate              Constant mutation rate.
CoolingFactory          Configure the cooling schedule of the
                        acceptance function of a genetic algorithm.
Cross2Gene              Import for examples.
CrossGene               Import for examples.
CrossRateFactory        Configure the crossover function of a genetic
                        algorithm.
ExponentialAdditiveCooling
                        Exponential additive cooling.
ExponentialMultiplicativeCooling
                        Exponential multiplicative cooling.
IACRate                 Individually adaptive crossover rate.
IAMBitRate              Individually adaptive mutation rate. (Bit
                        mutation Rate)
IAMRate                 Individually adaptive mutation rate.
InitGene                Import for examples.
LogarithmicMultiplicativeCooling
                        Logarithmic multiplicative cooling.
MClapply                MultiCore apply of library parallel.
MClapplyHet             MultiCore apply of library parallel for
                        heterogenous tasks.
MetropolisAcceptanceProbability
                        Metropolis acceptance probability.
MetropolisTable         Metropolis acceptance probability table.
MutationRateFactory     Configure the mutation rate function of a
                        genetic algorithm.
PowerAdditiveCooling    Power additive cooling.
PowerMultiplicativeCooling
                        Power multiplicative cooling.
PparLapply              uses parLapply of library parallel for using
                        workers on machines in a local network.
PparLapplyHet           uses parLapplyLB of library parallel for using
                        workers on machines in a local network.
ReplicateGene           Import for examples.
TerminationFactory      Configure the termination condition(s) a
                        genetic algorithm.
TrigonometricAdditiveCooling
                        Trigonometric additive cooling.
asPipeline              Converts a population into a list of genetic
                        operator pipelines.
checkTerminateError     Check terminateError()
checkTerminatePAC       Check terminatePAC()
checkTerminatedFalse    Check terminatedFalse()
checkTerminationFactory
                        Configure consistency checks and adapt 'penv'
                        for terminationConditions.
futureLapply            Future apply of R-package 'future.apply'.
futureLapplyHet         Future apply of R-package 'future.apply'
                        configured for a tasks with heterogenous
                        execution times.
lFxegaGaGene            Import for examples.
terminateAbsoluteError
                        Terminates, if the absolute deviation from the
                        global optimum is small.
terminateGEQ            Terminates, if the solution is greater equal a
                        threshold.
terminateLEQ            Terminates, if the solution is less equal a
                        threshold.
terminatePAC            Terminates if relative deviation from estimated
                        PAC bound for optimum is small. Works at 0.
terminateRelativeError
                        Terminates, if the relative deviation from the
                        global optimum is small.
terminateRelativeErrorZero
                        Terminates if relative deviation from optimum
                        is small. Works at 0.
terminatedFalse         No termination condition.
xegaBestGeneInPopulation
                        Extracts indices of best genes in population.
xegaBestInPopulation    Best solution in the population.
xegaConfiguration       Remembers R command command with which
                        algorithm has been called.
xegaEvalPopulation      Evaluates a population of genes in a problem
                        environment
xegaEvalPopulationFactory
                        Configures the evaluation of the population of
                        a genetic algorithm.
xegaInitPopulation      Initializes a population of genes.
xegaLogEvalsPopulation
                        Combine fitness, generations, and the phenotype
                        of the gene.
xegaNextPopulation      Computes the next population of genes.
xegaObservePopulation   Observe summary statistics of the fitness of
                        the population.
xegaPopulation          Package xegaPopulation.
xegaRepEvalPopulation   Evaluates a population of genes in a a problem
                        environment repeatedly.
xegaRepairPop           Repairs the list structure of a population of
                        genes.
xegaSummaryPopulation   Provide elementary summary statistics of the
                        fitness of the population.
