PHP Classes

File: travel.php

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  Classes of Ravindu Taveesha   PHP Genetic Algorithm Class   travel.php   Download  
File: travel.php
Role: Example script
Content type: text/plain
Description: travel example
Class: PHP Genetic Algorithm Class
Optimize order of sequences with Genetic algorithm
Author: By
Last change:
Date: 8 years ago
Size: 2,114 bytes
 

Contents

Class file image Download
<?php

//problem,
//Try to find suitable three cities by given cities using interest percentage of users
//and cities adventure, historical and environmental values to arrange trip.

require_once('galgo.php');

//object class
class City {
    var
$adventure;
    var
$history;
    var
$enviorment;
    
    function
City($adventure=0,$history=0,$enviorment=0) {
       
$this->adventure = $adventure;
       
$this->history = $history;
       
$this->enviorment = $enviorment;
    }
}

//assume total of properties = 10;
$anuradhapura = new City(1,8,1); //32
$nuwaraeliya = new City(4,1,5); //36
$mahanuwara = new City(1,6,2); //27
$sinharaja = new City(0,2,7); //13
$mathara = new City(5,2,3); //44
$kataharagama = new City(2,3,5); //28
$polonnaruwa = new City(1,3,7); //27
$hikkduwa = new City(6,0,4); //46
$galle = new City(5,1,4); //42
$amapara = new City(2,4,4); //30

//town lists
$towns = array($anuradhapura,$nuwaraeliya,$mahanuwara,$sinharaja,$mathara,$kataharagama,$polonnaruwa,$hikkduwa,$galle, $amapara);

//select random population
for ($i = 0; $i < 10 ; $i++)
{
    foreach(
array_rand($towns, 3) as $key){
       
$objects[] = $towns[$key];
    }
   
   
$population[] = array_slice($objects, $i, 3);
}


//This will be the fitness function.
function fitnessFunction($obj) {
   
   
$adventurePrecentage = 7;
   
$enviormentPrecentage = 3;
   
$historyPrecentage = 1;
   
    foreach(
$obj as $key => $objs){
       
$fitnessValue += (($objs->adventure * $adventurePrecentage) + ($objs->history * $historyPrecentage) + ($objs->enviorment * $enviormentPrecentage) );
    }
   
    return
$fitnessValue;
}

$galgo = new GAlgo();

$galgo->population = $population;
$galgo->generations = 10;
$galgo->mutationProbability = 10;
$galgo->fitnessFunction = 'fitnessFunction';
$galgo->evolve();


//no use for genetic
function debug($x) {
    echo
"<pre style='border: 1px solid black'>";
   
print_r($x);
    echo
'</pre>';
}

?>