rbga: R Based Genetic Algorithm (floating point chromosome)

Description Usage Arguments References See Also Examples

View source: R/rbga.R

Description

A R based genetic algorithm that optimizes, using a user set evaluation function, a set of floats. It takes as input minimum and maximum values for the floats to optimizes. The optimum is the chromosome for which the evaluation value is minimal.

It requires a evalFunc method to be supplied that takes as argument the chromosome, a vector of floats. Additionally, the GA optimization can be monitored by setting a monitorFunc that takes a rbga object as argument.

Results can be visualized with plot.rbga and summarized with summary.rbga.

Usage

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rbga(stringMin=c(), stringMax=c(),
     suggestions=NULL,
     popSize=200, iters=100,
     mutationChance=NA,
     elitism=NA,
     monitorFunc=NULL, evalFunc=NULL,
     showSettings=FALSE, verbose=FALSE)

Arguments

stringMin

vector with minimum values for each gene.

stringMax

vector with maximum values for each gene.

suggestions

optional list of suggested chromosomes

popSize

the population size.

iters

the number of iterations.

mutationChance

the chance that a gene in the chromosome mutates. By default 1/(size+1). It affects the convergence rate and the probing of search space: a low chance results in quicker convergence, while a high chance increases the span of the search space.

elitism

the number of chromosomes that are kept into the next generation. By default is about 20% of the population size.

monitorFunc

Method run after each generation to allow monitoring of the optimization

evalFunc

User supplied method to calculate the evaluation function for the given chromosome

showSettings

if true the settings will be printed to screen. By default False.

verbose

if true the algorithm will be more verbose. By default False.

References

C.B. Lucasius and G. Kateman (1993). Understanding and using genetic algorithms - Part 1. Concepts, properties and context. Chemometrics and Intelligent Laboratory Systems 19:1-33.

C.B. Lucasius and G. Kateman (1994). Understanding and using genetic algorithms - Part 2. Representation, configuration and hybridization. Chemometrics and Intelligent Laboratory Systems 25:99-145.

See Also

rbga.bin plot.rbga

Examples

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# optimize two values to match pi and sqrt(50)
evaluate <- function(string=c()) {
    returnVal = NA;
    if (length(string) == 2) {
        returnVal = abs(string[1]-pi) + abs(string[2]-sqrt(50));
    } else {
        stop("Expecting a chromosome of length 2!");
    }
    returnVal
}

monitor <- function(obj) {
    # plot the population
    xlim = c(obj$stringMin[1], obj$stringMax[1]);
    ylim = c(obj$stringMin[2], obj$stringMax[2]);
    plot(obj$population, xlim=xlim, ylim=ylim, 
    xlab="pi", ylab="sqrt(50)");
}

rbga.results = rbga(c(1, 1), c(5, 10), monitorFunc=monitor, 
    evalFunc=evaluate, verbose=TRUE, mutationChance=0.01)

plot(rbga.results)
plot(rbga.results, type="hist")
plot(rbga.results, type="vars")

Example output

Testing the sanity of parameters...
Not showing GA settings...
Starting with random values in the given domains...
Starting iteration 1 
Calucating evaluation values... ........................................................................................................................................................................................................ done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 4 mutations applied
Starting iteration 2 
Calucating evaluation values... ........................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 4 mutations applied
Starting iteration 3 
Calucating evaluation values... ............................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 6 mutations applied
Starting iteration 4 
Calucating evaluation values... .................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 5 mutations applied
Starting iteration 5 
Calucating evaluation values... .................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 4 mutations applied
Starting iteration 6 
Calucating evaluation values... .............................................................. done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 4 mutations applied
Starting iteration 7 
Calucating evaluation values... ........................................................ done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 3 mutations applied
Starting iteration 8 
Calucating evaluation values... ...................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 4 mutations applied
Starting iteration 9 
Calucating evaluation values... ............................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 4 mutations applied
Starting iteration 10 
Calucating evaluation values... ............................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 1 mutations applied
Starting iteration 11 
Calucating evaluation values... ........................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 1 mutations applied
Starting iteration 12 
Calucating evaluation values... ........................................................ done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 2 mutations applied
Starting iteration 13 
Calucating evaluation values... .............................................. done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 2 mutations applied
Starting iteration 14 
Calucating evaluation values... .................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 3 mutations applied
Starting iteration 15 
Calucating evaluation values... ........................................................ done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 3 mutations applied
Starting iteration 16 
Calucating evaluation values... ...................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 7 mutations applied
Starting iteration 17 
Calucating evaluation values... ............................................................. done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 2 mutations applied
Starting iteration 18 
Calucating evaluation values... ...................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 2 mutations applied
Starting iteration 19 
Calucating evaluation values... ........................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 4 mutations applied
Starting iteration 20 
Calucating evaluation values... ........................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 2 mutations applied
Starting iteration 21 
Calucating evaluation values... ............................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 3 mutations applied
Starting iteration 22 
Calucating evaluation values... ........................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 4 mutations applied
Starting iteration 23 
Calucating evaluation values... ..................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 5 mutations applied
Starting iteration 24 
Calucating evaluation values... ................................................ done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 3 mutations applied
Starting iteration 25 
Calucating evaluation values... ...................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 5 mutations applied
Starting iteration 26 
Calucating evaluation values... .......................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 5 mutations applied
Starting iteration 27 
Calucating evaluation values... .................................................................. done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 2 mutations applied
Starting iteration 28 
Calucating evaluation values... ...................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 3 mutations applied
Starting iteration 29 
Calucating evaluation values... ........................................................ done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 3 mutations applied
Starting iteration 30 
Calucating evaluation values... ................................................................. done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 5 mutations applied
Starting iteration 31 
Calucating evaluation values... ...................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 4 mutations applied
Starting iteration 32 
Calucating evaluation values... ..................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 4 mutations applied
Starting iteration 33 
Calucating evaluation values... ............................................................ done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 4 mutations applied
Starting iteration 34 
Calucating evaluation values... ....................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 4 mutations applied
Starting iteration 35 
Calucating evaluation values... ......................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 1 mutations applied
Starting iteration 36 
Calucating evaluation values... .................................................................. done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 3 mutations applied
Starting iteration 37 
Calucating evaluation values... ............................................................. done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 3 mutations applied
Starting iteration 38 
Calucating evaluation values... ................................................. done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 3 mutations applied
Starting iteration 39 
Calucating evaluation values... .................................................. done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 3 mutations applied
Starting iteration 40 
Calucating evaluation values... ........................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 1 mutations applied
Starting iteration 41 
Calucating evaluation values... ......................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 2 mutations applied
Starting iteration 42 
Calucating evaluation values... ..................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 3 mutations applied
Starting iteration 43 
Calucating evaluation values... ......................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 4 mutations applied
Starting iteration 44 
Calucating evaluation values... .......................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 3 mutations applied
Starting iteration 45 
Calucating evaluation values... ................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 3 mutations applied
Starting iteration 46 
Calucating evaluation values... ..................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 2 mutations applied
Starting iteration 47 
Calucating evaluation values... ................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 3 mutations applied
Starting iteration 48 
Calucating evaluation values... ..................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 4 mutations applied
Starting iteration 49 
Calucating evaluation values... ................................................. done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 4 mutations applied
Starting iteration 50 
Calucating evaluation values... ..................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 2 mutations applied
Starting iteration 51 
Calucating evaluation values... .................................................................. done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 3 mutations applied
Starting iteration 52 
Calucating evaluation values... .......................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 4 mutations applied
Starting iteration 53 
Calucating evaluation values... ................................................................. done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 1 mutations applied
Starting iteration 54 
Calucating evaluation values... ................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 3 mutations applied
Starting iteration 55 
Calucating evaluation values... ...................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 3 mutations applied
Starting iteration 56 
Calucating evaluation values... ........................................................ done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 2 mutations applied
Starting iteration 57 
Calucating evaluation values... .................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 2 mutations applied
Starting iteration 58 
Calucating evaluation values... ..................................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 3 mutations applied
Starting iteration 59 
Calucating evaluation values... ............................................................. done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 4 mutations applied
Starting iteration 60 
Calucating evaluation values... ........................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 5 mutations applied
Starting iteration 61 
Calucating evaluation values... ........................................................ done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 2 mutations applied
Starting iteration 62 
Calucating evaluation values... ....................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 2 mutations applied
Starting iteration 63 
Calucating evaluation values... ............................................................ done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 1 mutations applied
Starting iteration 64 
Calucating evaluation values... ................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 4 mutations applied
Starting iteration 65 
Calucating evaluation values... ............................................ done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 3 mutations applied
Starting iteration 66 
Calucating evaluation values... ........................................................ done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 3 mutations applied
Starting iteration 67 
Calucating evaluation values... ............................................................. done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 3 mutations applied
Starting iteration 68 
Calucating evaluation values... ............................................................ done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 4 mutations applied
Starting iteration 69 
Calucating evaluation values... ............................................................ done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 0 mutations applied
Starting iteration 70 
Calucating evaluation values... ........................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 7 mutations applied
Starting iteration 71 
Calucating evaluation values... ................................................................ done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 6 mutations applied
Starting iteration 72 
Calucating evaluation values... ...................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 4 mutations applied
Starting iteration 73 
Calucating evaluation values... ............................................................ done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 0 mutations applied
Starting iteration 74 
Calucating evaluation values... ......................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 4 mutations applied
Starting iteration 75 
Calucating evaluation values... ....................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 4 mutations applied
Starting iteration 76 
Calucating evaluation values... .................................................. done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 5 mutations applied
Starting iteration 77 
Calucating evaluation values... ................................................. done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 3 mutations applied
Starting iteration 78 
Calucating evaluation values... ....................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 2 mutations applied
Starting iteration 79 
Calucating evaluation values... ................................................................. done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 5 mutations applied
Starting iteration 80 
Calucating evaluation values... .......................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 1 mutations applied
Starting iteration 81 
Calucating evaluation values... .............................................. done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 2 mutations applied
Starting iteration 82 
Calucating evaluation values... ........................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 3 mutations applied
Starting iteration 83 
Calucating evaluation values... ............................................................ done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 6 mutations applied
Starting iteration 84 
Calucating evaluation values... ......................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 3 mutations applied
Starting iteration 85 
Calucating evaluation values... ................................................ done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 6 mutations applied
Starting iteration 86 
Calucating evaluation values... ................................................................ done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 1 mutations applied
Starting iteration 87 
Calucating evaluation values... ............................................. done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 2 mutations applied
Starting iteration 88 
Calucating evaluation values... ....................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 7 mutations applied
Starting iteration 89 
Calucating evaluation values... ........................................................................ done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 2 mutations applied
Starting iteration 90 
Calucating evaluation values... ..................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 0 mutations applied
Starting iteration 91 
Calucating evaluation values... ........................................................ done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 3 mutations applied
Starting iteration 92 
Calucating evaluation values... .................................................. done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 0 mutations applied
Starting iteration 93 
Calucating evaluation values... ............................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 6 mutations applied
Starting iteration 94 
Calucating evaluation values... ................................................. done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 6 mutations applied
Starting iteration 95 
Calucating evaluation values... .......................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 5 mutations applied
Starting iteration 96 
Calucating evaluation values... ....................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 2 mutations applied
Starting iteration 97 
Calucating evaluation values... ......................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 2 mutations applied
Starting iteration 98 
Calucating evaluation values... ........................................................ done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 7 mutations applied
Starting iteration 99 
Calucating evaluation values... ........................................................... done.
Sending current state to rgba.monitor()...
Creating next generation...
  sorting results...
  applying elitism...
  applying crossover...
  applying mutations... 1 mutations applied
Starting iteration 100 
Calucating evaluation values... ............................................................ done.
Sending current state to rgba.monitor()...

genalg documentation built on May 30, 2017, 4:41 a.m.

Related to rbga in genalg...