population_size = 100;
chromosome_length = 500;
generations = 500;
mutation_rate = 0.001;

best_fitness_hist = [];

%create inital population
population = initialization(population_size, chromosome_length);

for g = 1:generations
    %eval fitness
    fitness = sum(population, 2);
    %select individuals for tournament selection
    selected = tournament_selection(population,fitness,population_size);
    %crossover the individuals
    offspring = crossover(selected);
    %mutation
    mutated_offspring = mutate(offspring, mutation_rate);

    %create new population
    population = mutated_offspring;

    %display best fitness of this generation
    best_fitness = max(fitness);

    if best_fitness == chromosome_length
        break
    end

    best_fitness_hist = [best_fitness_hist;best_fitness];
    fprintf('Generation %d: Bestfitness = %d\n', g, best_fitness);
end

plot(best_fitness_hist)