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遗传算法的详细描述文档,文档中附带一定的代码解释

       new_genera[second][i+1] = temp[2][i]; <br>
     } <br>
 } <br>
      for(j=1; j<=(int) P5/2; j++) <br>
 { <br>
   first = find_parent(live,pop_size); <br>
   second = find_parent(live,pop_size); <br>
   new_genera[first][1] = 1.0; <br>
   new_genera[second][1] = 1.0; <br>

   for(i=1; i<=x2_vari; i++) <br>
     { <br>
       temp[1][i] = new_genera[first][i+1]; <br>
       temp[2][i] = new_genera[second][i+1]; <br>
     } <br>
   oper5(temp[1],temp[2],STEP,rc,fin_mat); <br>
   for(i=1; i<=x2_vari; i++) <br>
     { <br>
       new_genera[first][i+1] = temp[1][i]; <br>
       new_genera[second][i+1] = temp[2][i]; <br>
     } <br>
 } <br>
      for(j=1; j<=P6; j++) <br>
 { <br>
   first = find_parent(live,pop_size); <br>
   new_genera[first][1] = 1.0; <br>
   for(i=1; i<=x2_vari; i++) <br>
     t_vec[i] = new_genera[first][i+1]; <br>
   oper6(t_vec,fin_mat,rc,generations,count_gener,B); <br>
   for(i=1; i<=x2_vari; i++) <br>
     new_genera[first][i+1] = t_vec[i]; <br>
 } <br>
 } <br>
      k = 1; <br>
      for(i=1; i<=pop_size; i++) <br>
 if(die[i] != 0) <br>
   { <br>
     while(new_genera[k][1] != 1.0) <br>
       k++; <br>
     for(j=1; j<=x2_vari; j++) <br>
       population[i][j] = new_genera[k][j+1]; <br>
     k++; <br>
   } <br>
      for(i=1; i<=pop_size; i++) <br>
 { <br>
          if(tot_eq != 0) <br>
     { <br>
   for(j=1; j<=x2_vari + tot_eq; j++) <br>
     X[j] = 0.0; <br>
   find_X(fin_mat,population[i],X,x2_vari,tot_eq,x1,x2,a1_b); <br>
   for(j=1; j<=x2_vari + tot_eq; j++) <br>
     print_pop[i][j] = X[j]; <br>
 } <br>
            else <br>
            for(j=1; j<=x2_vari; j++) <br>

              print_pop[i][j] = X[j] = population[i][j]; <br>
          eval[i] = evaluate(X); <br>
 } <br>
      sort(MinMax,eval,population,pop_size,x2_vari); <br>
      switch(MinMax) <br>
 { <br>
 case 0: <br>
   if(Teval > eval[1]) <br>
     { <br>
       fprintf(output,"Generation #%d; the current best value is %f\n",count <br>
_gener,eval[1]); <br>
       Teval = eval[1]; <br>
     } <br>
   break; <br>
 case 1: <br>
   if(Teval < eval[1]) <br>
     { <br>
       fprintf(output,"Generation #%d; the current best value is %f\n",count <br>
_gener,eval[1]); <br>
       Teval = eval[1]; <br>
     } <br>
   break; <br>
   break; <br>
      } <br>
      count_gener++; <br>
    }while(count_gener <= generations); <br>
  fprintf(output,"\n\nTHE FINAL BEST VALUE FOUND IS: %f\n\n\n",eval[1]); <br>