}
}
if (file_exists('../modules/philhealth/class.philhealth.php')) {
include '../modules/philhealth/class.philhealth.php';
$philhealth = new philhealth;
if (!$module->activated('philhealth') && $initmod) {
$philhealth->init_sql();
$philhealth->init_menu();
$philhealth->init_deps();
$philhealth->init_lang();
$philhealth->init_help();
}
}
if (file_exists('../modules/population/class.population.php')) {
include '../modules/population/class.population.php';
$population = new population;
if (!$module->activated('population') && $initmod) {
$population->init_sql();
$population->init_menu();
$population->init_deps();
$population->init_lang();
$population->init_help();
}
}
if (file_exists('../modules/ptgroup/class.ptgroup.php')) {
include '../modules/ptgroup/class.ptgroup.php';
$ptgroup = new ptgroup;
if (!$module->activated('ptgroup') && $initmod) {
$ptgroup->init_sql();
$ptgroup->init_menu();
$ptgroup->init_deps();
private static function poolSelection($pop)
{
// Create a pool population
$pool = new population(algorithm::$poolSize, false);
for ($i = 0; $i < algorithm::$poolSize; $i++) {
$randomId = rand(0, $pop->size() - 1);
//Get a random individual from anywhere in the population
$pool->saveIndividual($i, $pop->getIndividual($randomId));
}
// Get the fittest
$fittest = $pool->getFittest();
return $fittest;
}
echo "\n\\ \\_\\ \\ ___/| | \\ ___/| | | \\ \\___ ";
echo "\n\\______ /\\___ >___| /\\___ >__| |__|\\___ >";
echo "\n \\/ \\/ \\/ \\/ \\/ ";
echo "\n-----------------------------------------------";
echo "\nUniformRate (crosssover point where to break gene string) :" . algorithm::$uniformRate;
echo "\nmutationRate (what % of genes change for each mutate) :" . algorithm::$mutationRate;
echo "\nPoolSize (crossover # of individuals to select in each pool ):" . algorithm::$poolSize;
echo "\nInitial population # individuals:" . $initial_population_size;
echo "\nelitism (keep best individual each generation true=1) :" . algorithm::$elitism;
// Set a candidate solution static class
fitnesscalc::setSolution($solution_phrase);
echo "\nMax Fitness is :" . fitnesscalc::getMaxFitness();
echo "\n-----------------------------------------------";
// Create an initial population
$time1 = microtime(true);
$myPop = new population($initial_population_size, true);
// Evolve our population until we reach an optimum solution
while ($myPop->getFittest()->getFitness() > fitnesscalc::getMaxFitness()) {
$generationCount++;
$most_fit = $myPop->getFittest()->getFitness();
$myPop = algorithm::evolvePopulation($myPop);
//create a new generation
if ($most_fit < $most_fit_last) {
// echo " *** MOST FIT ".$most_fit." Most fit last".$most_fit_last;
echo "\n Generation: " . $generationCount . " (Stagnant:" . $generation_stagnant . ") Fittest: " . $most_fit . "/" . fitnesscalc::getMaxFitness();
echo " Best: " . $myPop->getFittest();
$most_fit_last = $most_fit;
$generation_stagnant = 0;
//reset stagnant generation counter
} else {
$generation_stagnant++;
