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Genetic Algorithms in PHP
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<?php | |
$POPULATION = array(); //population of individuals | |
$GEN_COUNT = 1; | |
$TEST_COUNT = 0; | |
$GENE_OPTIONS = "abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ !@#$%&*1234567890"; | |
if( isset($_GET['goal']) ){ | |
$GOAL = $_GET['goal']; | |
} else { | |
$GOAL = "Hello World!"; | |
} | |
$DNA_SIZE = strlen($GOAL); | |
if( isset($_GET['population_size'])){ | |
$POPULATION_SIZE = (int)$_GET['population_size']; | |
} else { | |
$POPULATION_SIZE = 100; | |
} | |
genInitPopulation(); | |
while (true) { | |
naturalSelection(); | |
recreatePopulation(); | |
} | |
//========================== FUNCTIONS ============================ | |
function mutate($s) { | |
global $DNA_SIZE; | |
$sample = randomIndividual(); | |
for ($i=0; $i<$DNA_SIZE; $i++) { | |
if (rand(0,100) == 100) { | |
$s[$i] = $sample[$i]; | |
} | |
} | |
return $s; | |
} | |
function reproduction($ia, $ib) | |
{ | |
global $DNA_SIZE; | |
$crosspoint = rand(0, $DNA_SIZE-1); | |
$ia_before_cp = substr($ia, 0, $crosspoint); | |
//$ia_after_cp = substr($ia[0], $crosspoint); | |
//$ib_before_cp = substr($ib[0], 0, $crosspoint); | |
$ib_after_cp = substr($ib, $crosspoint); | |
$child = $ia_before_cp.$ib_after_cp; | |
$child = mutate($child); | |
return array($child, fitness($child)); | |
} | |
function recreatePopulation() | |
{ | |
global $POPULATION, $POPULATION_SIZE, $GEN_COUNT; | |
//echo '* Recreating population by reproducing randomly...'."\n"; | |
$GEN_COUNT++; | |
$c = count($POPULATION); | |
for ($i=$c; $i<$POPULATION_SIZE; $i++) { | |
$a = rand(0, $c-1); | |
$b = rand(0, $c-1); | |
array_push($POPULATION, reproduction($POPULATION[$a][0], $POPULATION[$b][0])); | |
} | |
} | |
function naturalSelection() | |
{ | |
global $POPULATION, $POPULATION_SIZE, $GEN_COUNT; | |
//echo '* Natural selection...'."\n"; | |
usort($POPULATION, "cmp"); | |
array_splice($POPULATION, ceil($POPULATION_SIZE/2)); | |
echo '<p>Best fit gen '.$GEN_COUNT.': '.$POPULATION[0][0].' ('.$POPULATION[0][1].')'."</p>"; | |
} | |
function cmp($a, $b) | |
{ | |
if ($a[1] == $b[1]) return 0; | |
return ($a[1] > $b[1]) ? -1 : 1; | |
} | |
function genInitPopulation() | |
{ | |
global $POPULATION, $POPULATION_SIZE; | |
//echo '* Generating inital population...'."\n"; | |
for($i=0; $i<$POPULATION_SIZE; $i++) { | |
$individual = randomIndividual(); | |
array_push($POPULATION, array($individual,fitness($individual))); | |
} | |
} | |
function randomIndividual() | |
{ | |
global $DNA_SIZE, $GENE_OPTIONS; | |
$individual = ''; | |
for($i=0; $i<$DNA_SIZE; $i++) { | |
$individual .= str_shuffle($GENE_OPTIONS)[0]; | |
} | |
return $individual; | |
} | |
function fitness($individual) | |
{ | |
global $GEN_COUNT, $POPULATION_SIZE, $TEST_COUNT, $GOAL, $DNA_SIZE, $GENE_OPTIONS; | |
$TEST_COUNT++; | |
$delta = 0; | |
for($i=0; $i<strlen($individual); $i++) { | |
$delta -= abs(ord($GOAL[$i]) - ord($individual[$i])); | |
} | |
if ($delta == 0) { | |
echo "<p>".'Solution found in '.$GEN_COUNT.' generation(s) of '.$POPULATION_SIZE.' individual(s)!'."</p>"; | |
echo '<h1>'.$individual."</h1>"; | |
echo 'There was '.$TEST_COUNT.' tests performed'."\n"; | |
$gene_qty = strlen($GENE_OPTIONS); | |
$combinations = number_format(pow($gene_qty, $DNA_SIZE),0,',','.'); | |
echo "Out of {$gene_qty}^{$DNA_SIZE} possible combinations ({$combinations})"; | |
exit(); | |
} | |
return $delta; | |
} | |
?> | |
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