genetik algoritma örnek kod

genetikAlgoritma.cpp

#pragma warning(disable:4786)        // disable debug warning
 
#include <iostream>                    // for cout etc.
#include <vector>                    // for vector class
#include <string>                    // for string class
#include <algorithm>                // for sort algorithm
#include <time.h>                    // for random seed
#include <math.h>                    // for abs()
 
#define GA_POPSIZE        2048        // ga population size
#define GA_MAXITER        16384        // maximum iterations
#define GA_ELITRATE        0.10f        // elitism rate
#define GA_MUTATIONRATE    0.25f        // mutation rate
#define GA_MUTATION        RAND_MAX * GA_MUTATIONRATE
#define GA_TARGET        std::string("Hello world!")
 
using namespace std;                // polluting global namespace, but hey...
 
struct ga_struct 
{
    string str;                        // the string
    unsigned int fitness;            // its fitness
};
 
typedef vector<ga_struct> ga_vector;// for brevity
 
void init_population(ga_vector &population,
                     ga_vector &buffer ) 
{
    int tsize = GA_TARGET.size();
 
    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
    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)
{ 
 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
        sort_by_fitness(*population);    // sort them
        print_best(*population);        // print the best one
 
        if ((*population)[0].fitness == 0) break;
 
        mate(*population, *buffer);        // mate the population together
        swap(population, buffer);        // swap buffers
    }
 
    return 0;
}