[C con Clase] ayuda con este codigo ALGORITMO GENETICO

[mario Guzman Moreno]

ola por favor alguien me puede explicar lo mas importante de este codigo, es un ejemplo de algoritmo genetico por cierto muy interesante, estoy empezando hacer mi tesis sobre AGs y no entiendo mucho este codigo
gracias de antemano

#pragma warning(disable:4786)        // disable debug warning  DESACTIVAR LA ALERTA DE DEPURACION

#include <iostream>                    // for cout etc.
#include <vector>                    // for vector class
#include <string>                    // for string class
#include <algorithm>                // for sort algorithm PARA ALGORITMO DE ORDENACION
#include <time.h>                    // for random seed
#include <math.h>                    // for abs()
#include <stdio.h>
#include <conio.h>                   //getch()

#define GA_POPSIZE        2048        // ga population size  TAMAÑO DE LA POBLACION
#define GA_MAXITER        16384        // maximum iterations  MAXIMO DE ITERACIONES
#define GA_ELITRATE        0.10f        // elitism rate    TASA DE ELITISMO
#define GA_MUTATIONRATE    0.25f        // mutation rate   LA TASA DE MUTACION
#define GA_MUTATION        RAND_MAX * GA_MUTATIONRATE
#define GA_TARGET        std::string("Hola Mario!")

using namespace std;                // polluting global namespace, but hey...
int i=0;
struct ga_struct 
{
    string str;                        // the string      LA CADENA
    unsigned int fitness;            // its fitness    SU APTITUD
};

typedef vector<ga_struct> ga_vector;// for brevity      PARA ABREVIAR

void init_population(ga_vector &population,
                     ga_vector &buffer ) 
{
    int tsize = GA_TARGET.size();
     cout << tsize;

    for (int i=0; i<GA_POPSIZE; i++) {
        ga_struct citizen;
        
        citizen.fitness = 0;
        citizen.str.erase();

        for (int j=0; j<tsize; j++)
            citizen.str += (rand() % 90) + 32;

        population.push_back(citizen);
    }

    buffer.resize(GA_POPSIZE);
}

void calc_fitness(ga_vector &population)
{
    string target = GA_TARGET;
    int tsize = target.size();
    unsigned int fitness;

    for (int i=0; i<GA_POPSIZE; i++) {
        fitness = 0;
        for (int j=0; j<tsize; j++) {
            fitness += abs(int(population[i].str[j] - target[j]));
        }
        
        population[i].fitness = fitness;
    }
}

bool fitness_sort(ga_struct x, ga_struct y) 
{ return (x.fitness < y.fitness); }

inline void sort_by_fitness(ga_vector &population)
{ sort(population.begin(), population.end(), fitness_sort); }

void elitism(ga_vector &population, 
                ga_vector &buffer, int esize )
{
    for (int i=0; i<esize; i++) {
        buffer[i].str = population[i].str;
        buffer[i].fitness = population[i].fitness;
    }
}

void mutate(ga_struct &member)
{
    int tsize = GA_TARGET.size();
    int ipos = rand() % tsize;
    int delta = (rand() % 90) + 32;

    member.str[ipos] = ((member.str[ipos] + delta) % 122);
}

void mate(ga_vector &population, ga_vector &buffer)
{
    int esize = GA_POPSIZE * GA_ELITRATE;
    int tsize = GA_TARGET.size(), spos, i1, i2;

    elitism(population, buffer, esize);

    // Mate the rest         MATE EL RESTO
    for (int i=esize; i<GA_POPSIZE; i++) {
        i1 = rand() % (GA_POPSIZE / 2);
        i2 = rand() % (GA_POPSIZE / 2);
        spos = rand() % tsize;

        buffer[i].str = population[i1].str.substr(0, spos) + 
                        population[i2].str.substr(spos, esize - spos);

        if (rand() < GA_MUTATION) mutate(buffer[i]);
    }
}

inline void print_best(ga_vector &gav)

{
 i++;
 cout << i;
 cout << " Best: " << gav[0].str << " (" << gav[0].fitness << ")" << endl;
 }

inline void swap(ga_vector *&population,
                 ga_vector *&buffer)
{ ga_vector *temp = population; population = buffer; buffer = temp; }

int main()
{
    srand(unsigned(time(NULL)));

    ga_vector pop_alpha, pop_beta;
    ga_vector *population, *buffer;

    init_population(pop_alpha, pop_beta);
    population = &pop_alpha;
    buffer = &pop_beta;

    for (int i=0; i<GA_MAXITER; i++) {
        calc_fitness(*population);        // calculate fitness CÁLCULO DE LA APTITUD
        sort_by_fitness(*population);    // sort them        ORDENARLOS
        print_best(*population);        // print the best one  INPRIME EL MEJOR

        if ((*population)[0].fitness == 0) break;



        mate(*population, *buffer);        // mate the population together
        swap(population, buffer);        // swap buffers  BUFFERS DE INTERCAMBIO
    }
 getch();

    return 0;
}

 


 		 	   		  
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