Task: Evolutionary algorithm
C++: #include <string>
#include <cstdlib>
#include <iostream>
#include <cassert>
#include <algorithm>
#include <vector>
#include <ctime>

std::string allowed_chars = " ABCDEFGHIJKLMNOPQRSTUVWXYZ";






class selection
{
public:
  
  
  
  
  static int fitness(std::string candidate)
  {
    assert(target.length() == candidate.length());

    int fitness_so_far = 0;

    for (int i = 0; i < target.length(); ++i)
    {
      int target_pos = allowed_chars.find(target[i]);
      int candidate_pos = allowed_chars.find(candidate[i]);
      int diff = std::abs(target_pos - candidate_pos);
      fitness_so_far -= std::min(diff, int(allowed_chars.length()) - diff);
    }

    return fitness_so_far;
  }

  
  static int target_length() { return target.length(); }
private:
  static std::string target;
};

std::string selection::target = "METHINKS IT IS LIKE A WEASEL";


void move_char(char& c, int distance)
{
  while (distance < 0)
    distance += allowed_chars.length();
  int char_pos = allowed_chars.find(c);
  c = allowed_chars[(char_pos + distance) % allowed_chars.length()];
}



std::string mutate(std::string parent, double mutation_rate)
{
  for (int i = 0; i < parent.length(); ++i)
    if (std::rand()/(RAND_MAX + 1.0) < mutation_rate)
    {
      int distance = std::rand() % 3 + 1;
      if(std::rand()%2 == 0)
        move_char(parent[i], distance);
      else
        move_char(parent[i], -distance);
    }
  return parent;
}



bool less_fit(std::string const& s1, std::string const& s2)
{
  return selection::fitness(s1) < selection::fitness(s2);
}

int main()
{
  int const C = 100;

  std::srand(time(0));

  std::string parent;
  for (int i = 0; i < selection::target_length(); ++i)
  {
    parent += allowed_chars[std::rand() % allowed_chars.length()];
  }

  int const initial_fitness = selection::fitness(parent);

  for(int fitness = initial_fitness;
      fitness < 0;
      fitness = selection::fitness(parent))
  {
    std::cout << parent << ": " << fitness << "\n";
    double const mutation_rate = 0.02 + (0.9*fitness)/initial_fitness;
    std::vector<std::string> childs;
    childs.reserve(C+1);

    childs.push_back(parent);
    for (int i = 0; i < C; ++i)
      childs.push_back(mutate(parent, mutation_rate));

    parent = *std::max_element(childs.begin(), childs.end(), less_fit);
  }
  std::cout << "final string: " << parent << "\n";
}

PHP: define('TARGET','METHINKS IT IS LIKE A WEASEL');
define('TBL','ABCDEFGHIJKLMNOPQRSTUVWXYZ ');

define('MUTATE',15);
define('COPIES',30);
define('TARGET_COUNT',strlen(TARGET));
define('TBL_COUNT',strlen(TBL));


function unfitness($a,$b)
{
        $sum=0;
        for($i=0;$i<strlen($a);$i++)
                if($a[$i]!=$b[$i]) $sum++;
        return($sum);
}

function mutate($a)
{
        $tbl=TBL;
        for($i=0;$i<strlen($a);$i++) $out[$i]=mt_rand(0,MUTATE)?$a[$i]:$tbl[mt_rand(0,TBL_COUNT-1)];
        return(implode('',$out));
}


$tbl=TBL;
for($i=0;$i<TARGET_COUNT;$i++) $tspec[$i]=$tbl[mt_rand(0,TBL_COUNT-1)];
$parent[0]=implode('',$tspec);
$best=TARGET_COUNT+1;
$iters=0;
do {
        for($i=1;$i<COPIES;$i++) $parent[$i]=mutate($parent[0]);

        for($best_i=$i=0; $i<COPIES;$i++) {
                $unfit=unfitness(TARGET,$parent[$i]);
                if($unfit < $best || !$i) {
                        $best=$unfit;
                        $best_i=$i;
                }
        }
        if($best_i>0) $parent[0]=$parent[$best_i];
        $iters++;
        print("Generation $iters, score $best: $parent[0]\n");
} while($best);