GA.m

function GA(target,population_size,mutation_rate)

% menginisialisasi populasi
population = create_population(target, population_size);

islooping = true;
generation = 0;
while islooping
    % evaluation
    islooping = evaluation(population);
    % display
    logging(population,target,generation)
    % selection
    [parent1,parent2] = selection(population);
    % crossover
    [child1,child2] = crossover(parent1,parent2);
    % mutation
    mutant1 = mutation(child1, mutation_rate);
    mutant2 = mutation(child2, mutation_rate);
    % hitung fitness mutant
    mutant1.fitness = calculate_fitness(mutant1.genes,target);
    mutant2.fitness = calculate_fitness(mutant2.genes,target);
    % membuat new generation
    children = [mutant1 mutant2];
    population = regeneration(children,population);
    generation = generation + 1;
end
end