devolve

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devolve


class  ListGA(T, uint PopSize, alias fitness, alias generator, alias selector = topPar!(cast(uint)(PopSize * 0.1)), alias crossover = singlePoint, alias mutator = randomSwap, alias comp = "a > b"): SimpleGA!(T, PopSize, comp, fitness, generator, selector, crossover, mutator);

Genetic algorithm for genomes in the form of a list. This includes dynamic and statically sized arrays.

Parameters
T Type representing the genome. Should be a dynamic or statically sized array
PopSize The size of the population
fitness User defined fitness function. Must return double
generator Function used to create new members of the population
selector Selection method used to pick parents of next generation.
crossover Used to crossover individuals to create the new generation.
mutator Used to alter the population.
comp Used to determine whether a larger or smaller fitness is better.
Examples
//Grow individual with greatest sum
import devolve, std.algorithm;
alias genomeType = int[4];

double fitness(genomeType ind) {return reduce!"a+b"(ind)}

void main() {

    auto ga = new ListGA!(genomeType, 10, fitness, preset!(1, 2, 3, 4));
    //converges rapidly on [4, 4, 4, 4]
    ga.evolve(100);
}

this();

Default constructor. No statistics will be printed, and mutation will be set at 1%, crossover rate at 80%

this(float mutRate, float crossoverRate, uint statFreq);

Convienience constructor, equivilant to default constructing and setting mutation rate and statistic frequency